Information-theoretic methods for estimating of complicated probability distributions

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Zong, Zhi

2006-01-01

Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based methods for estimating complicated probability distributions. Estimating probability distribution of a random variable is the fundamental task for quite some fields besides statistics, such as reliability, probabilistic risk analysis (PSA), machine learning, pattern recognization, image processing, neur

Multivariate normal tissue complication probability modeling of gastrointestinal toxicity after external beam radiotherapy for localized prostate cancer

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Cella, Laura; D’Avino, Vittoria; Liuzzi, Raffaele; Conson, Manuel; Doria, Francesca; Faiella, Adriana; Loffredo, Filomena; Salvatore, Marco; Pacelli, Roberto

2013-01-01

The risk of radio-induced gastrointestinal (GI) complications is affected by several factors other than the dose to the rectum such as patient characteristics, hormonal or antihypertensive therapy, and acute rectal toxicity. Purpose of this work is to study clinical and dosimetric parameters impacting on late GI toxicity after prostate external beam radiotherapy (RT) and to establish multivariate normal tissue complication probability (NTCP) model for radiation-induced GI complications. A total of 57 men who had undergone definitive RT for prostate cancer were evaluated for GI events classified using the RTOG/EORTC scoring system. Their median age was 73 years (range 53–85). The patients were assessed for GI toxicity before, during, and periodically after RT completion. Several clinical variables along with rectum dose-volume parameters (Vx) were collected and their correlation to GI toxicity was analyzed by Spearman’s rank correlation coefficient (Rs). Multivariate logistic regression method using resampling techniques was applied to select model order and parameters for NTCP modeling. Model performance was evaluated through the area under the receiver operating characteristic curve (AUC). At a median follow-up of 30 months, 37% (21/57) patients developed G1-2 acute GI events while 33% (19/57) were diagnosed with G1-2 late GI events. An NTCP model for late mild/moderate GI toxicity based on three variables including V65 (OR = 1.03), antihypertensive and/or anticoagulant (AH/AC) drugs (OR = 0.24), and acute GI toxicity (OR = 4.3) was selected as the most predictive model (Rs = 0.47, p < 0.001; AUC = 0.79). This three-variable model outperforms the logistic model based on V65 only (Rs = 0.28, p < 0.001; AUC = 0.69). We propose a logistic NTCP model for late GI toxicity considering not only rectal irradiation dose but also clinical patient-specific factors. Accordingly, the risk of G1-2 late GI increases as V65 increases, it is higher for patients experiencing

Optimization of radiation therapy, III: a method of assessing complication probabilities from dose-volume histograms

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Lyman, J.T.; Wolbarst, A.B.

1987-01-01

To predict the likelihood of success of a therapeutic strategy, one must be able to assess the effects of the treatment upon both diseased and healthy tissues. This paper proposes a method for determining the probability that a healthy organ that receives a non-uniform distribution of X-irradiation, heat, chemotherapy, or other agent will escape complications. Starting with any given dose distribution, a dose-cumulative-volume histogram for the organ is generated. This is then reduced by an interpolation scheme (involving the volume-weighting of complication probabilities) to a slightly different histogram that corresponds to the same overall likelihood of complications, but which contains one less step. The procedure is repeated, one step at a time, until there remains a final, single-step histogram, for which the complication probability can be determined. The formalism makes use of a complication response function C(D, V) which, for the given treatment schedule, represents the probability of complications arising when the fraction V of the organ receives dose D and the rest of the organ gets none. Although the data required to generate this function are sparse at present, it should be possible to obtain the necessary information from in vivo and clinical studies. Volume effects are taken explicitly into account in two ways: the precise shape of the patient's histogram is employed in the calculation, and the complication response function is a function of the volume

Multivariate Normal Tissue Complication Probability Modeling of Heart Valve Dysfunction in Hodgkin Lymphoma Survivors

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Cella, Laura; Liuzzi, Raffaele; Conson, Manuel; D’Avino, Vittoria; Salvatore, Marco; Pacelli, Roberto

2013-01-01

Purpose: To establish a multivariate normal tissue complication probability (NTCP) model for radiation-induced asymptomatic heart valvular defects (RVD). Methods and Materials: Fifty-six patients treated with sequential chemoradiation therapy for Hodgkin lymphoma (HL) were retrospectively reviewed for RVD events. Clinical information along with whole heart, cardiac chambers, and lung dose distribution parameters was collected, and the correlations to RVD were analyzed by means of Spearman's rank correlation coefficient (Rs). For the selection of the model order and parameters for NTCP modeling, a multivariate logistic regression method using resampling techniques (bootstrapping) was applied. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). Results: When we analyzed the whole heart, a 3-variable NTCP model including the maximum dose, whole heart volume, and lung volume was shown to be the optimal predictive model for RVD (Rs = 0.573, P<.001, AUC = 0.83). When we analyzed the cardiac chambers individually, for the left atrium and for the left ventricle, an NTCP model based on 3 variables including the percentage volume exceeding 30 Gy (V30), cardiac chamber volume, and lung volume was selected as the most predictive model (Rs = 0.539, P<.001, AUC = 0.83; and Rs = 0.557, P<.001, AUC = 0.82, respectively). The NTCP values increase as heart maximum dose or cardiac chambers V30 increase. They also increase with larger volumes of the heart or cardiac chambers and decrease when lung volume is larger. Conclusions: We propose logistic NTCP models for RVD considering not only heart irradiation dose but also the combined effects of lung and heart volumes. Our study establishes the statistical evidence of the indirect effect of lung size on radio-induced heart toxicity

Prediction of radiation-induced liver disease by Lyman normal-tissue complication probability model in three-dimensional conformal radiation therapy for primary liver carcinoma

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Xu ZhiYong; Liang Shixiong; Zhu Ji; Zhu Xiaodong; Zhao Jiandong; Lu Haijie; Yang Yunli; Chen Long; Wang Anyu; Fu Xiaolong; Jiang Guoliang

2006-01-01

Purpose: To describe the probability of RILD by application of the Lyman-Kutcher-Burman normal-tissue complication (NTCP) model for primary liver carcinoma (PLC) treated with hypofractionated three-dimensional conformal radiotherapy (3D-CRT). Methods and Materials: A total of 109 PLC patients treated by 3D-CRT were followed for RILD. Of these patients, 93 were in liver cirrhosis of Child-Pugh Grade A, and 16 were in Child-Pugh Grade B. The Michigan NTCP model was used to predict the probability of RILD, and then the modified Lyman NTCP model was generated for Child-Pugh A and Child-Pugh B patients by maximum-likelihood analysis. Results: Of all patients, 17 developed RILD in which 8 were of Child-Pugh Grade A, and 9 were of Child-Pugh Grade B. The prediction of RILD by the Michigan model was underestimated for PLC patients. The modified n, m, TD 5 (1) were 1.1, 0.28, and 40.5 Gy and 0.7, 0.43, and 23 Gy for patients with Child-Pugh A and B, respectively, which yielded better estimations of RILD probability. The hepatic tolerable doses (TD 5 ) would be MDTNL of 21 Gy and 6 Gy, respectively, for Child-Pugh A and B patients. Conclusions: The Michigan model was probably not fit to predict RILD in PLC patients. A modified Lyman NTCP model for RILD was recommended

Calculation of the uncertainty in complication probability for various dose-response models, applied to the parotid gland

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Schilstra, C.; Meertens, H.

2001-01-01

Purpose: Usually, models that predict normal tissue complication probability (NTCP) are fitted to clinical data with the maximum likelihood (ML) method. This method inevitably causes a loss of information contained in the data. In this study, an alternative method is investigated that calculates the parameter probability distribution (PD), and, thus, conserves all information. The PD method also allows the calculation of the uncertainty in the NTCP, which is an (often-neglected) prerequisite for the intercomparison of both treatment plans and NTCP models. The PD and ML methods are applied to parotid gland data, and the results are compared. Methods and Materials: The drop in salivary flow due to radiotherapy was measured in 25 parotid glands of 15 patients. Together with the parotid gland dose-volume histograms (DVH), this enabled the calculation of the parameter PDs for three different NTCP models (Lyman, relative seriality, and critical volume). From these PDs, the NTCP and its uncertainty could be calculated for arbitrary parotid gland DVHs. ML parameters and resulting NTCP values were calculated also. Results: All models fitted equally well. The parameter PDs turned out to have nonnormal shapes and long tails. The NTCP predictions of the ML and PD method usually differed considerably, depending on the NTCP model and the nature of irradiation. NTCP curves and ML parameters suggested a highly parallel organization of the parotid gland. Conclusions: Considering the substantial differences between the NTCP predictions of the ML and PD method, the use of the PD method is preferred, because this is the only method that takes all information contained in the clinical data into account. Furthermore, PD method gives a true measure of the uncertainty in the NTCP

Normal Tissue Complication Probability Estimation by the Lyman-Kutcher-Burman Method Does Not Accurately Predict Spinal Cord Tolerance to Stereotactic Radiosurgery

International Nuclear Information System (INIS)

Daly, Megan E.; Luxton, Gary; Choi, Clara Y.H.; Gibbs, Iris C.; Chang, Steven D.; Adler, John R.; Soltys, Scott G.

2012-01-01

Purpose: To determine whether normal tissue complication probability (NTCP) analyses of the human spinal cord by use of the Lyman-Kutcher-Burman (LKB) model, supplemented by linear–quadratic modeling to account for the effect of fractionation, predict the risk of myelopathy from stereotactic radiosurgery (SRS). Methods and Materials: From November 2001 to July 2008, 24 spinal hemangioblastomas in 17 patients were treated with SRS. Of the tumors, 17 received 1 fraction with a median dose of 20 Gy (range, 18–30 Gy) and 7 received 20 to 25 Gy in 2 or 3 sessions, with cord maximum doses of 22.7 Gy (range, 17.8–30.9 Gy) and 22.0 Gy (range, 20.2–26.6 Gy), respectively. By use of conventional values for α/β, volume parameter n, 50% complication probability dose TD 50 , and inverse slope parameter m, a computationally simplified implementation of the LKB model was used to calculate the biologically equivalent uniform dose and NTCP for each treatment. Exploratory calculations were performed with alternate values of α/β and n. Results: In this study 1 case (4%) of myelopathy occurred. The LKB model using radiobiological parameters from Emami and the logistic model with parameters from Schultheiss overestimated complication rates, predicting 13 complications (54%) and 18 complications (75%), respectively. An increase in the volume parameter (n), to assume greater parallel organization, improved the predictive value of the models. Maximum-likelihood LKB fitting of α/β and n yielded better predictions (0.7 complications), with n = 0.023 and α/β = 17.8 Gy. Conclusions: The spinal cord tolerance to the dosimetry of SRS is higher than predicted by the LKB model using any set of accepted parameters. Only a high α/β value in the LKB model and only a large volume effect in the logistic model with Schultheiss data could explain the low number of complications observed. This finding emphasizes that radiobiological models traditionally used to estimate spinal cord NTCP

The use of normal tissue complication probability to predict radiation hepatitis

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Keum, Ki Chang; Seong, Jin Sil; Suh, Chang Ok; Lee, Sang Wook; Chung, Eun Ji; Shin, Hyun Soo; Kim, Gwi Eon

2000-01-01

Although it has been known that the tolerance of the liver to external beam irradiation depends on the irradiated volume and dose, few data exist which quantify this dependence. However, recently, with the development of three dimensional (3-D) treatment planning, have the tools to quantify the relationships between dose, volume, and normal tissue complications become available. The objective of this study is to investigate the relationships between normal tissue complication probability (NTCP) and the risk of radiation hepatitis for patients who received variant dose partial liver irradiation. From March 1992 to December 1994, 10 patients with hepatoma and 10 patients with bile duct cancer were included in this study. Eighteen patients had normal hepatic function, but 2 patients (prothrombin time 73%, 68%) had mild liver cirrhosis before irradiation. Radiation therapy was delivered with 10MV linear accelerator, 180-200 cGy fraction per day. The total dose ranged from 3,960 cGy to 6,000 cGy (median dose 5,040 cGy). The normal tissue complication probability was calculated by using Lyman's model. Radiation hepatitis was defined as the development of anicteric elevation of alkaline phosphatase of at least two fold and non-malignant ascites in the absence of documented progressive. The calculated NTCP ranged from 0.001 to 0.840 (median 0.05). Three of the 20 patients developed radiation hepatitis. The NTCP of the patients with radiation hepatitis were 0.390, 0.528, 0.844 (median: O.58±0.23), but that of the patients without radiation hepatitis ranged from 0.001 to 0.308 (median: 0.09±0.09). When the NTCP was calculated by using the volume factor of 0.32, a radiation hepatitis was observed only in patients with the NTCP value more than 0.39. By contrast, clinical results of evolving radiation hepatitis were not well correlated with NTCP value calculated when the volume factor of 0.69 was applied. On the basis of these observations, volume factor of 0.32 was more

A new formula for normal tissue complication probability (NTCP) as a function of equivalent uniform dose (EUD).

Science.gov (United States)

Luxton, Gary; Keall, Paul J; King, Christopher R

2008-01-07

To facilitate the use of biological outcome modeling for treatment planning, an exponential function is introduced as a simpler equivalent to the Lyman formula for calculating normal tissue complication probability (NTCP). The single parameter of the exponential function is chosen to reproduce the Lyman calculation to within approximately 0.3%, and thus enable easy conversion of data contained in empirical fits of Lyman parameters for organs at risk (OARs). Organ parameters for the new formula are given in terms of Lyman model m and TD(50), and conversely m and TD(50) are expressed in terms of the parameters of the new equation. The role of the Lyman volume-effect parameter n is unchanged from its role in the Lyman model. For a non-homogeneously irradiated OAR, an equation relates d(ref), n, v(eff) and the Niemierko equivalent uniform dose (EUD), where d(ref) and v(eff) are the reference dose and effective fractional volume of the Kutcher-Burman reduction algorithm (i.e. the LKB model). It follows in the LKB model that uniform EUD irradiation of an OAR results in the same NTCP as the original non-homogeneous distribution. The NTCP equation is therefore represented as a function of EUD. The inverse equation expresses EUD as a function of NTCP and is used to generate a table of EUD versus normal tissue complication probability for the Emami-Burman parameter fits as well as for OAR parameter sets from more recent data.

A new formula for normal tissue complication probability (NTCP) as a function of equivalent uniform dose (EUD)

International Nuclear Information System (INIS)

Luxton, Gary; Keall, Paul J; King, Christopher R

2008-01-01

To facilitate the use of biological outcome modeling for treatment planning, an exponential function is introduced as a simpler equivalent to the Lyman formula for calculating normal tissue complication probability (NTCP). The single parameter of the exponential function is chosen to reproduce the Lyman calculation to within ∼0.3%, and thus enable easy conversion of data contained in empirical fits of Lyman parameters for organs at risk (OARs). Organ parameters for the new formula are given in terms of Lyman model m and TD 50 , and conversely m and TD 50 are expressed in terms of the parameters of the new equation. The role of the Lyman volume-effect parameter n is unchanged from its role in the Lyman model. For a non-homogeneously irradiated OAR, an equation relates d ref , n, v eff and the Niemierko equivalent uniform dose (EUD), where d ref and v eff are the reference dose and effective fractional volume of the Kutcher-Burman reduction algorithm (i.e. the LKB model). It follows in the LKB model that uniform EUD irradiation of an OAR results in the same NTCP as the original non-homogeneous distribution. The NTCP equation is therefore represented as a function of EUD. The inverse equation expresses EUD as a function of NTCP and is used to generate a table of EUD versus normal tissue complication probability for the Emami-Burman parameter fits as well as for OAR parameter sets from more recent data

Hypothyroidism after primary radiotherapy for head and neck squamous cell carcinoma: Normal tissue complication probability modeling with latent time correction

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Rønjom, Marianne Feen; Brink, Carsten; Bentzen, Søren M.; Hegedüs, Laszlo; Overgaard, Jens; Johansen, Jørgen

2013-01-01

Background and purpose: To develop a normal tissue complication probability (NTCP) model of radiation-induced biochemical hypothyroidism (HT) after primary radiotherapy for head and neck squamous cell carcinoma (HNSCC) with adjustment for latency and clinical risk factors. Patients and methods: Patients with HNSCC receiving definitive radiotherapy with 66–68 Gy without surgery were followed up with serial post-treatment thyrotropin (TSH) assessment. HT was defined as TSH >4.0 mU/l. Data were analyzed with both a logistic and a mixture model (correcting for latency) to determine risk factors for HT and develop an NTCP model based on mean thyroid dose (MTD) and thyroid volume. Results: 203 patients were included. Median follow-up: 25.1 months. Five-year estimated risk of HT was 25.6%. In the mixture model, the only independent risk factors for HT were thyroid volume (cm 3 ) (OR = 0.75 [95% CI: 0.64–0.85], p 3 , respectively. Conclusions: Comparing the logistic and mixture models demonstrates the importance of latent-time correction in NTCP-modeling. Thyroid dose constraints in treatment planning should be individualized based on thyroid volume

Normal tissue complication probability model parameter estimation for xerostomia in head and neck cancer patients based on scintigraphy and quality of life assessments

International Nuclear Information System (INIS)

Lee, Tsair-Fwu; Chao, Pei-Ju; Wang, Hung-Yu; Hsu, Hsuan-Chih; Chang, PaoShu; Chen, Wen-Cheng

2012-01-01

With advances in modern radiotherapy (RT), many patients with head and neck (HN) cancer can be effectively cured. However, xerostomia is a common complication in patients after RT for HN cancer. The purpose of this study was to use the Lyman–Kutcher–Burman (LKB) model to derive parameters for the normal tissue complication probability (NTCP) for xerostomia based on scintigraphy assessments and quality of life (QoL) questionnaires. We performed validation tests of the Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) guidelines against prospectively collected QoL and salivary scintigraphic data. Thirty-one patients with HN cancer were enrolled. Salivary excretion factors (SEFs) measured by scintigraphy and QoL data from self-reported questionnaires were used for NTCP modeling to describe the incidence of grade 3 + xerostomia. The NTCP parameters estimated from the QoL and SEF datasets were compared. Model performance was assessed using Pearson’s chi-squared test, Nagelkerke’s R 2 , the area under the receiver operating characteristic curve, and the Hosmer–Lemeshow test. The negative predictive value (NPV) was checked for the rate of correctly predicting the lack of incidence. Pearson’s chi-squared test was used to test the goodness of fit and association. Using the LKB NTCP model and assuming n=1, the dose for uniform irradiation of the whole or partial volume of the parotid gland that results in 50% probability of a complication (TD 50 ) and the slope of the dose–response curve (m) were determined from the QoL and SEF datasets, respectively. The NTCP-fitted parameters for local disease were TD 50 =43.6 Gy and m=0.18 with the SEF data, and TD 50 =44.1 Gy and m=0.11 with the QoL data. The rate of grade 3 + xerostomia for treatment plans meeting the QUANTEC guidelines was specifically predicted, with a NPV of 100%, using either the QoL or SEF dataset. Our study shows the agreement between the NTCP parameter modeling based on SEF and

Normal tissue complication probability model parameter estimation for xerostomia in head and neck cancer patients based on scintigraphy and quality of life assessments

Science.gov (United States)

2012-01-01

Background With advances in modern radiotherapy (RT), many patients with head and neck (HN) cancer can be effectively cured. However, xerostomia is a common complication in patients after RT for HN cancer. The purpose of this study was to use the Lyman–Kutcher–Burman (LKB) model to derive parameters for the normal tissue complication probability (NTCP) for xerostomia based on scintigraphy assessments and quality of life (QoL) questionnaires. We performed validation tests of the Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) guidelines against prospectively collected QoL and salivary scintigraphic data. Methods Thirty-one patients with HN cancer were enrolled. Salivary excretion factors (SEFs) measured by scintigraphy and QoL data from self-reported questionnaires were used for NTCP modeling to describe the incidence of grade 3+ xerostomia. The NTCP parameters estimated from the QoL and SEF datasets were compared. Model performance was assessed using Pearson’s chi-squared test, Nagelkerke’s R2, the area under the receiver operating characteristic curve, and the Hosmer–Lemeshow test. The negative predictive value (NPV) was checked for the rate of correctly predicting the lack of incidence. Pearson’s chi-squared test was used to test the goodness of fit and association. Results Using the LKB NTCP model and assuming n=1, the dose for uniform irradiation of the whole or partial volume of the parotid gland that results in 50% probability of a complication (TD50) and the slope of the dose–response curve (m) were determined from the QoL and SEF datasets, respectively. The NTCP-fitted parameters for local disease were TD50=43.6 Gy and m=0.18 with the SEF data, and TD50=44.1 Gy and m=0.11 with the QoL data. The rate of grade 3+ xerostomia for treatment plans meeting the QUANTEC guidelines was specifically predicted, with a NPV of 100%, using either the QoL or SEF dataset. Conclusions Our study shows the agreement between the NTCP

Normal tissue complication probability model parameter estimation for xerostomia in head and neck cancer patients based on scintigraphy and quality of life assessments

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Lee Tsair-Fwu

2012-12-01

Full Text Available Abstract Background With advances in modern radiotherapy (RT, many patients with head and neck (HN cancer can be effectively cured. However, xerostomia is a common complication in patients after RT for HN cancer. The purpose of this study was to use the Lyman–Kutcher–Burman (LKB model to derive parameters for the normal tissue complication probability (NTCP for xerostomia based on scintigraphy assessments and quality of life (QoL questionnaires. We performed validation tests of the Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC guidelines against prospectively collected QoL and salivary scintigraphic data. Methods Thirty-one patients with HN cancer were enrolled. Salivary excretion factors (SEFs measured by scintigraphy and QoL data from self-reported questionnaires were used for NTCP modeling to describe the incidence of grade 3+ xerostomia. The NTCP parameters estimated from the QoL and SEF datasets were compared. Model performance was assessed using Pearson’s chi-squared test, Nagelkerke’s R2, the area under the receiver operating characteristic curve, and the Hosmer–Lemeshow test. The negative predictive value (NPV was checked for the rate of correctly predicting the lack of incidence. Pearson’s chi-squared test was used to test the goodness of fit and association. Results Using the LKB NTCP model and assuming n=1, the dose for uniform irradiation of the whole or partial volume of the parotid gland that results in 50% probability of a complication (TD50 and the slope of the dose–response curve (m were determined from the QoL and SEF datasets, respectively. The NTCP-fitted parameters for local disease were TD50=43.6 Gy and m=0.18 with the SEF data, and TD50=44.1 Gy and m=0.11 with the QoL data. The rate of grade 3+ xerostomia for treatment plans meeting the QUANTEC guidelines was specifically predicted, with a NPV of 100%, using either the QoL or SEF dataset. Conclusions Our study shows the agreement

Analysis of clinical complication data for radiation hepatitis using a parallel architecture model

International Nuclear Information System (INIS)

Jackson, A.; Haken, R.K. ten; Robertson, J.M.; Kessler, M.L.; Kutcher, G.J.; Lawrence, T.S.

1995-01-01

Purpose: The detailed knowledge of dose volume distributions available from the three-dimensional (3D) conformal radiation treatment of tumors in the liver (reported elsewhere) offers new opportunities to quantify the effect of volume on the probability of producing radiation hepatitis. We aim to test a new parallel architecture model of normal tissue complication probability (NTCP) with these data. Methods and Materials: Complication data and dose volume histograms from a total of 93 patients with normal liver function, treated on a prospective protocol with 3D conformal radiation therapy and intraarterial hepatic fluorodeoxyuridine, were analyzed with a new parallel architecture model. Patient treatment fell into six categories differing in doses delivered and volumes irradiated. By modeling the radiosensitivity of liver subunits, we are able to use dose volume histograms to calculate the fraction of the liver damaged in each patient. A complication results if this fraction exceeds the patient's functional reserve. To determine the patient distribution of functional reserves and the subunit radiosensitivity, the maximum likelihood method was used to fit the observed complication data. Results: The parallel model fit the complication data well, although uncertainties on the functional reserve distribution and subunit radiosensitivy are highly correlated. Conclusion: The observed radiation hepatitis complications show a threshold effect that can be described well with a parallel architecture model. However, additional independent studies are required to better determine the parameters defining the functional reserve distribution and subunit radiosensitivity

Probabilities of Pulmonary and Cardiac Complications and Radiographic Parameters in Breast Cancer Radiotherapy

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Noh, O Kyu; Paek, Sung Ho; Ahn, Seung Do; Choi, Eun Kyung; Lee, Sang Wook; Song, Si Yeol; Yoon, Sang Min; Kim, Jong Hoon [Dept. of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul (Korea, Republic of)

2010-11-15

To evaluate the relationship between the normal tissue complication probability (NTCP) of 3- dimensional (3-D) radiotherapy and the radiographic parameters of 2-dimensional (2-D) radiotherapy such as central lung distance (CLD) and maximal heart distance (MHD). We analyzed 110 patients who were treated with postoperative radiotherapy for breast cancer. A two-field tangential technique, a three-field technique, and the reverse hockey stick method were used. The radiation dose administered to whole breast or the chest wall was 50.4 Gy, whereas a 45 Gy was administered to the supraclavicular field. The NTCPs of the heart and lung were calculated by the modified Lyman model and the relative seriality model. For all patients, the NTCPs of radiation-induced pneumonitis and cardiac mortality were 0.5% and 0.7%, respectively. The NTCP of radiation-induced pneumonitis was higher in patients treated with the reverse hockey stick method than in those treated by other two techniques (0.0%, 0.0%, 3.1%, p<0.001). The NTCP of radiation-induced pneumonitis increased with CLD. The NTCP of cardiac mortality increased with MHD (R2=0.808). We found a close correlation between the NTCP of 3-D radiotherapy and 2-D radiographic parameters. Our results are useful to reanalyze the previous 2-D based clinical reports about breast radiation therapy complications as a viewpoint of NTCP.

Probabilities of Pulmonary and Cardiac Complications and Radiographic Parameters in Breast Cancer Radiotherapy

International Nuclear Information System (INIS)

Noh, O Kyu; Paek, Sung Ho; Ahn, Seung Do; Choi, Eun Kyung; Lee, Sang Wook; Song, Si Yeol; Yoon, Sang Min; Kim, Jong Hoon

2010-01-01

To evaluate the relationship between the normal tissue complication probability (NTCP) of 3- dimensional (3-D) radiotherapy and the radiographic parameters of 2-dimensional (2-D) radiotherapy such as central lung distance (CLD) and maximal heart distance (MHD). We analyzed 110 patients who were treated with postoperative radiotherapy for breast cancer. A two-field tangential technique, a three-field technique, and the reverse hockey stick method were used. The radiation dose administered to whole breast or the chest wall was 50.4 Gy, whereas a 45 Gy was administered to the supraclavicular field. The NTCPs of the heart and lung were calculated by the modified Lyman model and the relative seriality model. For all patients, the NTCPs of radiation-induced pneumonitis and cardiac mortality were 0.5% and 0.7%, respectively. The NTCP of radiation-induced pneumonitis was higher in patients treated with the reverse hockey stick method than in those treated by other two techniques (0.0%, 0.0%, 3.1%, p<0.001). The NTCP of radiation-induced pneumonitis increased with CLD. The NTCP of cardiac mortality increased with MHD (R2=0.808). We found a close correlation between the NTCP of 3-D radiotherapy and 2-D radiographic parameters. Our results are useful to reanalyze the previous 2-D based clinical reports about breast radiation therapy complications as a viewpoint of NTCP.

Normal tissue complication probability modeling for cochlea constraints to avoid causing tinnitus after head-and-neck intensity-modulated radiation therapy

International Nuclear Information System (INIS)

Lee, Tsair-Fwu; Yeh, Shyh-An; Chao, Pei-Ju; Chang, Liyun; Chiu, Chien-Liang; Ting, Hui-Min; Wang, Hung-Yu; Huang, Yu-Jie

2015-01-01

Radiation-induced tinnitus is a side effect of radiotherapy in the inner ear for cancers of the head and neck. Effective dose constraints for protecting the cochlea are under-reported. The aim of this study is to determine the cochlea dose limitation to avoid causing tinnitus after head-and-neck cancer (HNC) intensity-modulated radiation therapy (IMRT). In total 211 patients with HNC were included; the side effects of radiotherapy were investigated for 422 inner ears in the cohort. Forty-nine of the four hundred and twenty-two samples (11.6 %) developed grade 2+ tinnitus symptoms after IMRT, as diagnosed by a clinician. The Late Effects of Normal Tissues–Subjective, Objective, Management, Analytic (LENT-SOMA) criteria were used for tinnitus evaluation. The logistic and Lyman-Kutcher-Burman (LKB) normal tissue complication probability (NTCP) models were used for the analyses. The NTCP-fitted parameters were TD 50 = 46.31 Gy (95 % CI, 41.46–52.50), γ 50 = 1.27 (95 % CI, 1.02–1.55), and TD 50 = 46.52 Gy (95 % CI, 41.91–53.43), m = 0.35 (95 % CI, 0.30–0.42) for the logistic and LKB models, respectively. The suggested guideline TD 20 for the tolerance dose to produce a 20 % complication rate within a specific period of time was TD 20 = 33.62 Gy (95 % CI, 30.15–38.27) (logistic) and TD 20 = 32.82 Gy (95 % CI, 29.58–37.69) (LKB). To maintain the incidence of grade 2+ tinnitus toxicity <20 % in IMRT, we suggest that the mean dose to the cochlea should be <32 Gy. However, models should not be extrapolated to other patient populations without further verification and should first be confirmed before clinical implementation

The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

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Defraene, Gilles; Van den Bergh, Laura; Al-Mamgani, Abrahim; Haustermans, Karin; Heemsbergen, Wilma; Van den Heuvel, Frank; Lebesque, Joos V.

2012-01-01

Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including the most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011–0.013) clinical factor was “previous abdominal surgery.” As second significant (p = 0.012–0.016) factor, “cardiac history” was included in all three rectal bleeding fits, whereas including “diabetes” was significant (p = 0.039–0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003–0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D 50 . Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints. Conclusions

The Benefits of Including Clinical Factors in Rectal Normal Tissue Complication Probability Modeling After Radiotherapy for Prostate Cancer

Energy Technology Data Exchange (ETDEWEB)

Defraene, Gilles, E-mail: gilles.defraene@uzleuven.be [Radiation Oncology Department, University Hospitals Leuven, Leuven (Belgium); Van den Bergh, Laura [Radiation Oncology Department, University Hospitals Leuven, Leuven (Belgium); Al-Mamgani, Abrahim [Department of Radiation Oncology, Erasmus Medical Center - Daniel den Hoed Cancer Center, Rotterdam (Netherlands); Haustermans, Karin [Radiation Oncology Department, University Hospitals Leuven, Leuven (Belgium); Heemsbergen, Wilma [Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands); Van den Heuvel, Frank [Radiation Oncology Department, University Hospitals Leuven, Leuven (Belgium); Lebesque, Joos V. [Netherlands Cancer Institute - Antoni van Leeuwenhoek Hospital, Amsterdam (Netherlands)

2012-03-01

Purpose: To study the impact of clinical predisposing factors on rectal normal tissue complication probability modeling using the updated results of the Dutch prostate dose-escalation trial. Methods and Materials: Toxicity data of 512 patients (conformally treated to 68 Gy [n = 284] and 78 Gy [n = 228]) with complete follow-up at 3 years after radiotherapy were studied. Scored end points were rectal bleeding, high stool frequency, and fecal incontinence. Two traditional dose-based models (Lyman-Kutcher-Burman (LKB) and Relative Seriality (RS) and a logistic model were fitted using a maximum likelihood approach. Furthermore, these model fits were improved by including the most significant clinical factors. The area under the receiver operating characteristic curve (AUC) was used to compare the discriminating ability of all fits. Results: Including clinical factors significantly increased the predictive power of the models for all end points. In the optimal LKB, RS, and logistic models for rectal bleeding and fecal incontinence, the first significant (p = 0.011-0.013) clinical factor was 'previous abdominal surgery.' As second significant (p = 0.012-0.016) factor, 'cardiac history' was included in all three rectal bleeding fits, whereas including 'diabetes' was significant (p = 0.039-0.048) in fecal incontinence modeling but only in the LKB and logistic models. High stool frequency fits only benefitted significantly (p = 0.003-0.006) from the inclusion of the baseline toxicity score. For all models rectal bleeding fits had the highest AUC (0.77) where it was 0.63 and 0.68 for high stool frequency and fecal incontinence, respectively. LKB and logistic model fits resulted in similar values for the volume parameter. The steepness parameter was somewhat higher in the logistic model, also resulting in a slightly lower D{sub 50}. Anal wall DVHs were used for fecal incontinence, whereas anorectal wall dose best described the other two endpoints

Impact of Chemotherapy on Normal Tissue Complication Probability Models of Acute Hematologic Toxicity in Patients Receiving Pelvic Intensity Modulated Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Bazan, Jose G.; Luxton, Gary; Kozak, Margaret M.; Anderson, Eric M.; Hancock, Steven L.; Kapp, Daniel S.; Kidd, Elizabeth A.; Koong, Albert C.; Chang, Daniel T., E-mail: dtchang@stanford.edu

2013-12-01

Purpose: To determine how chemotherapy agents affect radiation dose parameters that correlate with acute hematologic toxicity (HT) in patients treated with pelvic intensity modulated radiation therapy (P-IMRT) and concurrent chemotherapy. Methods and Materials: We assessed HT in 141 patients who received P-IMRT for anal, gynecologic, rectal, or prostate cancers, 95 of whom received concurrent chemotherapy. Patients were separated into 4 groups: mitomycin (MMC) + 5-fluorouracil (5FU, 37 of 141), platinum ± 5FU (Cis, 32 of 141), 5FU (26 of 141), and P-IMRT alone (46 of 141). The pelvic bone was contoured as a surrogate for pelvic bone marrow (PBM) and divided into subsites: ilium, lower pelvis, and lumbosacral spine (LSS). The volumes of each region receiving 5-40 Gy were calculated. The endpoint for HT was grade ≥3 (HT3+) leukopenia, neutropenia or thrombocytopenia. Normal tissue complication probability was calculated using the Lyman-Kutcher-Burman model. Logistic regression was used to analyze association between HT3+ and dosimetric parameters. Results: Twenty-six patients experienced HT3+: 10 of 37 (27%) MMC, 14 of 32 (44%) Cis, 2 of 26 (8%) 5FU, and 0 of 46 P-IMRT. PBM dosimetric parameters were correlated with HT3+ in the MMC group but not in the Cis group. LSS dosimetric parameters were well correlated with HT3+ in both the MMC and Cis groups. Constrained optimization (0model resulted in n=1, m = 0.11, TD{sub 50} = 31 Gy for LSS in the MMC group and n=1, m = 0.27, TD{sub 50} = 35 Gy for LSS in the Cis group. Conclusions: The incidence of HT3+ depends on type of chemotherapy received. Patients receiving P-IMRT ± 5FU have better bone marrow tolerance than those receiving irradiation concurrent with either Cis or MMC. Treatment with MMC has a lower TD{sub 50} and more steeply rising normal tissue complication probability curve compared with treatment with Cis. Dose tolerance of PBM and the LSS subsite may be lower for

Model uncertainty: Probabilities for models?

International Nuclear Information System (INIS)

Winkler, R.L.

1994-01-01

Like any other type of uncertainty, model uncertainty should be treated in terms of probabilities. The question is how to do this. The most commonly-used approach has a drawback related to the interpretation of the probabilities assigned to the models. If we step back and look at the big picture, asking what the appropriate focus of the model uncertainty question should be in the context of risk and decision analysis, we see that a different probabilistic approach makes more sense, although it raise some implementation questions. Current work that is underway to address these questions looks very promising

Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia.

Science.gov (United States)

Gabryś, Hubert S; Buettner, Florian; Sterzing, Florian; Hauswald, Henrik; Bangert, Mark

2018-01-01

The purpose of this study is to investigate whether machine learning with dosiomic, radiomic, and demographic features allows for xerostomia risk assessment more precise than normal tissue complication probability (NTCP) models based on the mean radiation dose to parotid glands. A cohort of 153 head-and-neck cancer patients was used to model xerostomia at 0-6 months (early), 6-15 months (late), 15-24 months (long-term), and at any time (a longitudinal model) after radiotherapy. Predictive power of the features was evaluated by the area under the receiver operating characteristic curve (AUC) of univariate logistic regression models. The multivariate NTCP models were tuned and tested with single and nested cross-validation, respectively. We compared predictive performance of seven classification algorithms, six feature selection methods, and ten data cleaning/class balancing techniques using the Friedman test and the Nemenyi post hoc analysis. NTCP models based on the parotid mean dose failed to predict xerostomia (AUCs  0.85), dose gradients in the right-left (AUCs > 0.78), and the anterior-posterior (AUCs > 0.72) direction. Multivariate models of long-term xerostomia were typically based on the parotid volume, the parotid eccentricity, and the dose-volume histogram (DVH) spread with the generalization AUCs ranging from 0.74 to 0.88. On average, support vector machines and extra-trees were the top performing classifiers, whereas the algorithms based on logistic regression were the best choice for feature selection. We found no advantage in using data cleaning or class balancing methods. We demonstrated that incorporation of organ- and dose-shape descriptors is beneficial for xerostomia prediction in highly conformal radiotherapy treatments. Due to strong reliance on patient-specific, dose-independent factors, our results underscore the need for development of personalized data-driven risk profiles for NTCP models of xerostomia. The facilitated

Multiple-event probability in general-relativistic quantum mechanics. II. A discrete model

International Nuclear Information System (INIS)

Mondragon, Mauricio; Perez, Alejandro; Rovelli, Carlo

2007-01-01

We introduce a simple quantum mechanical model in which time and space are discrete and periodic. These features avoid the complications related to continuous-spectrum operators and infinite-norm states. The model provides a tool for discussing the probabilistic interpretation of generally covariant quantum systems, without the confusion generated by spurious infinities. We use the model to illustrate the formalism of general-relativistic quantum mechanics, and to test the definition of multiple-event probability introduced in a companion paper [Phys. Rev. D 75, 084033 (2007)]. We consider a version of the model with unitary time evolution and a version without unitary time evolution

Incidence of late rectal bleeding in high-dose conformal radiotherapy of prostate cancer using equivalent uniform dose-based and dose-volume-based normal tissue complication probability models

International Nuclear Information System (INIS)

Soehn, Matthias; Yan Di; Liang Jian; Meldolesi, Elisa; Vargas, Carlos; Alber, Markus

2007-01-01

Purpose: Accurate modeling of rectal complications based on dose-volume histogram (DVH) data are necessary to allow safe dose escalation in radiotherapy of prostate cancer. We applied different equivalent uniform dose (EUD)-based and dose-volume-based normal tissue complication probability (NTCP) models to rectal wall DVHs and follow-up data for 319 prostate cancer patients to identify the dosimetric factors most predictive for Grade ≥ 2 rectal bleeding. Methods and Materials: Data for 319 patients treated at the William Beaumont Hospital with three-dimensional conformal radiotherapy (3D-CRT) under an adaptive radiotherapy protocol were used for this study. The following models were considered: (1) Lyman model and (2) logit-formula with DVH reduced to generalized EUD (3) serial reconstruction unit (RU) model (4) Poisson-EUD model, and (5) mean dose- and (6) cutoff dose-logistic regression model. The parameters and their confidence intervals were determined using maximum likelihood estimation. Results: Of the patients, 51 (16.0%) showed Grade 2 or higher bleeding. As assessed qualitatively and quantitatively, the Lyman- and Logit-EUD, serial RU, and Poisson-EUD model fitted the data very well. Rectal wall mean dose did not correlate to Grade 2 or higher bleeding. For the cutoff dose model, the volume receiving > 73.7 Gy showed most significant correlation to bleeding. However, this model fitted the data more poorly than the EUD-based models. Conclusions: Our study clearly confirms a volume effect for late rectal bleeding. This can be described very well by the EUD-like models, of which the serial RU- and Poisson-EUD model can describe the data with only two parameters. Dose-volume-based cutoff-dose models performed worse

An integrated logistic formula for prediction of complications from radiosurgery

International Nuclear Information System (INIS)

Flickinger, J.C.

1989-01-01

An integrated logistic model for predicting the probability of complications when small volumes of tissue receive an inhomogeneous radiation dose is described. This model can be used with either an exponential or linear quadratic correction for dose per fraction and time. Both the exponential and linear quadratic versions of this integrated logistic formula provide reasonable estimates of the tolerance of brain to radiosurgical dose distributions where there are small volumes of brain receiving high radiation doses and larger volumes receiving lower doses. This makes it possible to predict the probability of complications from stereotactic radiosurgery, as well as combinations of fractionated large volume irradiation with a radiosurgical boost. Complication probabilities predicted for single fraction radiosurgery with the Leksell Gamma Unit using 4, 8, 14, and 18 mm diameter collimators as well as for whole brain irradiation combined with a radiosurgical boost are presented. The exponential and linear quadratic versions of the integrated logistic formula provide useful methods of calculating the probability of complications from radiosurgical treatment

Investigation of normal tissue complication probabilities in prostate and partial breast irradiation radiotherapy techniques

International Nuclear Information System (INIS)

Bezak, E.; Takam, R.; Bensaleh, S.; Yeoh, E.; Marcu, L.

2011-01-01

Full text: Normal- Tissue-Complication Probabilities of rectum, bladder and urethra following various radiation techniques for prostate cancer were evaluated using the relative-seriality and Lyman models. NTCPs of lungs, heart and skin, their dependence on sourceposition, balloon-deformation were also investigated for HDR mammosite brachytherapy. The prostate treatment techniques included external three dimentional conformal-radiotherapy, Low-Dose-Rate brachytherapy (1-125), High-Dose-Rate brachytherapy (Ir-I92). Dose- Volume-Histograms of critical structures for prostate and breast radiotherapy, retrieved from corresponding treatment planning systems, were converted to Biological Effective Dose (BEffD)-based and Equivalent Dose(Deq)-based DVHs to account for differences in radiation delivery and fractionation schedule. Literature-based model parameters were used to calculate NTCPs. Hypofractionated 3D-CRT (2.75 Gy/fraction, total dose 55 Gy) NTCPs of rectum, bladder and urethra were less than those for standard fractionated 4-field 3D-CRT (2-Gy/fraction, 64 Gy) and dose-escalated 4- and 5-field 3D-CRT (74 Gy). Rectal and bladder NTCPs (5.2% and 6.6%) following the dose-escalated 4-field 3D-CRT (74 Gy) were the highest among analyzed techniques. The average NTCP for rectum and urethra were 0.6% and 24.7% for LDRBT and 0.5% and 11.2% for HDR-BT. For Mammosite, NTCP was estimated to be 0.1 %, 0.1 %, 1.2% and 3.5% for skin desquamation, erythema, telangiectasia and fibrosis respectively (the source positioned at the balloon centre). A 4 mm Mammosite-balloon deformation leads to overdosing of PTV regions by ∼40%, resulting in excessive skin dose and increased NTCP. Conclusions Prostate brachytherapy resulted in NTCPs lower compared to external beam techniques. Mammosite-brachytherapy resulted in no heart/lung complications regardless of balloon deformation. However, 4 mm deformation caused 0.6% increase in tissue fibrosis NTCP.

Development of a multivariable normal tissue complication probability (NTCP) model for tube feeding dependence after curative radiotherapy/chemo-radiotherapy in head and neck cancer

International Nuclear Information System (INIS)

Wopken, Kim; Bijl, Hendrik P.; Schaaf, Arjen van der; Laan, Hans Paul van der; Chouvalova, Olga; Steenbakkers, Roel J.H.M.; Doornaert, Patricia; Slotman, Ben J.; Oosting, Sjoukje F.; Christianen, Miranda E.M.C.; Laan, Bernard F.A.M. van der; Roodenburg, Jan L.N.; René Leemans, C.; Verdonck-de Leeuw, Irma M.; Langendijk, Johannes A.

2014-01-01

Background and purpose: Curative radiotherapy/chemo-radiotherapy for head and neck cancer (HNC) may result in severe acute and late side effects, including tube feeding dependence. The purpose of this prospective cohort study was to develop a multivariable normal tissue complication probability (NTCP) model for tube feeding dependence 6 months (TUBE M6 ) after definitive radiotherapy, radiotherapy plus cetuximab or concurrent chemoradiation based on pre-treatment and treatment characteristics. Materials and methods: The study included 355 patients with HNC. TUBE M6 was scored prospectively in a standard follow-up program. To design the prediction model, the penalized learning method LASSO was used, with TUBE M6 as the endpoint. Results: The prevalence of TUBE M6 was 10.7%. The multivariable model with the best performance consisted of the variables: advanced T-stage, moderate to severe weight loss at baseline, accelerated radiotherapy, chemoradiation, radiotherapy plus cetuximab, the mean dose to the superior and inferior pharyngeal constrictor muscle, to the contralateral parotid gland and to the cricopharyngeal muscle. Conclusions: We developed a multivariable NTCP model for TUBE M6 to identify patients at risk for tube feeding dependence. The dosimetric variables can be used to optimize radiotherapy treatment planning aiming at prevention of tube feeding dependence and to estimate the benefit of new radiation technologies

Calculating the Probability of Returning a Loan with Binary Probability Models

Directory of Open Access Journals (Sweden)

Julian Vasilev

2014-12-01

Full Text Available The purpose of this article is to give a new approach in calculating the probability of returning a loan. A lot of factors affect the value of the probability. In this article by using statistical and econometric models some influencing factors are proved. The main approach is concerned with applying probit and logit models in loan management institutions. A new aspect of the credit risk analysis is given. Calculating the probability of returning a loan is a difficult task. We assume that specific data fields concerning the contract (month of signing, year of signing, given sum and data fields concerning the borrower of the loan (month of birth, year of birth (age, gender, region, where he/she lives may be independent variables in a binary logistics model with a dependent variable “the probability of returning a loan”. It is proved that the month of signing a contract, the year of signing a contract, the gender and the age of the loan owner do not affect the probability of returning a loan. It is proved that the probability of returning a loan depends on the sum of contract, the remoteness of the loan owner and the month of birth. The probability of returning a loan increases with the increase of the given sum, decreases with the proximity of the customer, increases for people born in the beginning of the year and decreases for people born at the end of the year.

Modelling the probability of building fires

Directory of Open Access Journals (Sweden)

Vojtěch Barták

2014-12-01

Full Text Available Systematic spatial risk analysis plays a crucial role in preventing emergencies.In the Czech Republic, risk mapping is currently based on the risk accumulationprinciple, area vulnerability, and preparedness levels of Integrated Rescue Systemcomponents. Expert estimates are used to determine risk levels for individualhazard types, while statistical modelling based on data from actual incidents andtheir possible causes is not used. Our model study, conducted in cooperation withthe Fire Rescue Service of the Czech Republic as a model within the Liberec andHradec Králové regions, presents an analytical procedure leading to the creation ofbuilding fire probability maps based on recent incidents in the studied areas andon building parameters. In order to estimate the probability of building fires, aprediction model based on logistic regression was used. Probability of fire calculatedby means of model parameters and attributes of specific buildings can subsequentlybe visualized in probability maps.

Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia

Directory of Open Access Journals (Sweden)

Hubert S. Gabryś

2018-03-01

Full Text Available PurposeThe purpose of this study is to investigate whether machine learning with dosiomic, radiomic, and demographic features allows for xerostomia risk assessment more precise than normal tissue complication probability (NTCP models based on the mean radiation dose to parotid glands.Material and methodsA cohort of 153 head-and-neck cancer patients was used to model xerostomia at 0–6 months (early, 6–15 months (late, 15–24 months (long-term, and at any time (a longitudinal model after radiotherapy. Predictive power of the features was evaluated by the area under the receiver operating characteristic curve (AUC of univariate logistic regression models. The multivariate NTCP models were tuned and tested with single and nested cross-validation, respectively. We compared predictive performance of seven classification algorithms, six feature selection methods, and ten data cleaning/class balancing techniques using the Friedman test and the Nemenyi post hoc analysis.ResultsNTCP models based on the parotid mean dose failed to predict xerostomia (AUCs < 0.60. The most informative predictors were found for late and long-term xerostomia. Late xerostomia correlated with the contralateral dose gradient in the anterior–posterior (AUC = 0.72 and the right–left (AUC = 0.68 direction, whereas long-term xerostomia was associated with parotid volumes (AUCs > 0.85, dose gradients in the right–left (AUCs > 0.78, and the anterior–posterior (AUCs > 0.72 direction. Multivariate models of long-term xerostomia were typically based on the parotid volume, the parotid eccentricity, and the dose–volume histogram (DVH spread with the generalization AUCs ranging from 0.74 to 0.88. On average, support vector machines and extra-trees were the top performing classifiers, whereas the algorithms based on logistic regression were the best choice for feature selection. We found no advantage in using data cleaning or class balancing

Correlations and Non-Linear Probability Models

DEFF Research Database (Denmark)

Breen, Richard; Holm, Anders; Karlson, Kristian Bernt

2014-01-01

the dependent variable of the latent variable model and its predictor variables. We show how this correlation can be derived from the parameters of non-linear probability models, develop tests for the statistical significance of the derived correlation, and illustrate its usefulness in two applications. Under......Although the parameters of logit and probit and other non-linear probability models are often explained and interpreted in relation to the regression coefficients of an underlying linear latent variable model, we argue that they may also be usefully interpreted in terms of the correlations between...... certain circumstances, which we explain, the derived correlation provides a way of overcoming the problems inherent in cross-sample comparisons of the parameters of non-linear probability models....

The transition probabilities of the reciprocity model

NARCIS (Netherlands)

Snijders, T.A.B.

1999-01-01

The reciprocity model is a continuous-time Markov chain model used for modeling longitudinal network data. A new explicit expression is derived for its transition probability matrix. This expression can be checked relatively easily. Some properties of the transition probabilities are given, as well

Comparing linear probability model coefficients across groups

DEFF Research Database (Denmark)

Holm, Anders; Ejrnæs, Mette; Karlson, Kristian Bernt

2015-01-01

of the following three components: outcome truncation, scale parameters and distributional shape of the predictor variable. These results point to limitations in using linear probability model coefficients for group comparisons. We also provide Monte Carlo simulations and real examples to illustrate......This article offers a formal identification analysis of the problem in comparing coefficients from linear probability models between groups. We show that differences in coefficients from these models can result not only from genuine differences in effects, but also from differences in one or more...... these limitations, and we suggest a restricted approach to using linear probability model coefficients in group comparisons....

A probability space for quantum models

Science.gov (United States)

Lemmens, L. F.

2017-06-01

A probability space contains a set of outcomes, a collection of events formed by subsets of the set of outcomes and probabilities defined for all events. A reformulation in terms of propositions allows to use the maximum entropy method to assign the probabilities taking some constraints into account. The construction of a probability space for quantum models is determined by the choice of propositions, choosing the constraints and making the probability assignment by the maximum entropy method. This approach shows, how typical quantum distributions such as Maxwell-Boltzmann, Fermi-Dirac and Bose-Einstein are partly related with well-known classical distributions. The relation between the conditional probability density, given some averages as constraints and the appropriate ensemble is elucidated.

Calculation of complication probability of pion treatment at PSI using dose-volume histograms

International Nuclear Information System (INIS)

Nakagawa, Keiichi; Akanuma, Atsuo; Aoki, Yukimasa

1991-01-01

In the conformation technique a target volume is irradiated uniformly as in conventional radiations, whereas surrounding tissue and organs are nonuniformly irradiated. Clinical data on radiation injuries that accumulate with conventional radiation are not applicable without appropriate compensation. Recently a putative solution of this problem was proposed by Lyman using dose-volume histograms. This histogram reduction method reduces a given dose-volume histogram of an organ to a single step which corresponds to the equivalent complication probability by interpolation. As a result it converts nonuniform radiation into a unique dose to the whole organ which has the equivalent likelihood of radiation injury. This method is based on low LET radiation with conventional fractionation schedules. When it is applied to high LET radiation such as negative pion treatment, a high LET dose should be converted to an equivalent photon dose using an appropriate value of RBE. In the present study the histogram reduction method was applied to actual patients treated by the negative pion conformation technique at the Paul Scherrer Institute. Out of evaluable 90 cases of pelvic tumors, 16 developed grade III-IV bladder injury, and 7 developed grade III-IV rectal injury. The 90 cases were divided into roughly equal groups according to the equivalent doses to the entire bladder and rectum. Complication rates and equivalent doses to the full organs in these groups could be represented by a sigmoid dose-effect relation. When RBE from a pion dose to a photon dose is assumed to be 2.1 for bladder injury, the rates of bladder complications fit best to the theoretical complication curve. When the RBE value was 2.3, the rates of rectal injury fit the theoretical curve best. These values are close to the conversion factor of 2.0 that is used in clinical practice at PSI. This agreement suggests the clinical feasibility of the histogram reduction method in conformation radiotherapy. (author)

Dependency models and probability of joint events

International Nuclear Information System (INIS)

Oerjasaeter, O.

1982-08-01

Probabilistic dependencies between components/systems are discussed with reference to a broad classification of potential failure mechanisms. Further, a generalized time-dependency model, based on conditional probabilities for estimation of the probability of joint events and event sequences is described. The applicability of this model is clarified/demonstrated by various examples. It is concluded that the described model of dependency is a useful tool for solving a variety of practical problems concerning the probability of joint events and event sequences where common cause and time-dependent failure mechanisms are involved. (Auth.)

A new plan-scoring method using normal tissue complication probability for personalized treatment plan decisions in prostate cancer

Science.gov (United States)

Kim, Kwang Hyeon; Lee, Suk; Shim, Jang Bo; Yang, Dae Sik; Yoon, Won Sup; Park, Young Je; Kim, Chul Yong; Cao, Yuan Jie; Chang, Kyung Hwan

2018-01-01

The aim of this study was to derive a new plan-scoring index using normal tissue complication probabilities to verify different plans in the selection of personalized treatment. Plans for 12 patients treated with tomotherapy were used to compare scoring for ranking. Dosimetric and biological indexes were analyzed for the plans for a clearly distinguishable group ( n = 7) and a similar group ( n = 12), using treatment plan verification software that we developed. The quality factor ( QF) of our support software for treatment decisions was consistent with the final treatment plan for the clearly distinguishable group (average QF = 1.202, 100% match rate, n = 7) and the similar group (average QF = 1.058, 33% match rate, n = 12). Therefore, we propose a normal tissue complication probability (NTCP) based on the plan scoring index for verification of different plans for personalized treatment-plan selection. Scoring using the new QF showed a 100% match rate (average NTCP QF = 1.0420). The NTCP-based new QF scoring method was adequate for obtaining biological verification quality and organ risk saving using the treatment-planning decision-support software we developed for prostate cancer.

Model uncertainty and probability

International Nuclear Information System (INIS)

Parry, G.W.

1994-01-01

This paper discusses the issue of model uncertainty. The use of probability as a measure of an analyst's uncertainty as well as a means of describing random processes has caused some confusion, even though the two uses are representing different types of uncertainty with respect to modeling a system. The importance of maintaining the distinction between the two types is illustrated with a simple example

On the Inclusion of Short-distance Bystander Effects into a Logistic Tumor Control Probability Model.

Science.gov (United States)

Tempel, David G; Brodin, N Patrik; Tomé, Wolfgang A

2018-01-01

Currently, interactions between voxels are neglected in the tumor control probability (TCP) models used in biologically-driven intensity-modulated radiotherapy treatment planning. However, experimental data suggests that this may not always be justified when bystander effects are important. We propose a model inspired by the Ising model, a short-range interaction model, to investigate if and when it is important to include voxel to voxel interactions in biologically-driven treatment planning. This Ising-like model for TCP is derived by first showing that the logistic model of tumor control is mathematically equivalent to a non-interacting Ising model. Using this correspondence, the parameters of the logistic model are mapped to the parameters of an Ising-like model and bystander interactions are introduced as a short-range interaction as is the case for the Ising model. As an example, we apply the model to study the effect of bystander interactions in the case of radiation therapy for prostate cancer. The model shows that it is adequate to neglect bystander interactions for dose distributions that completely cover the treatment target and yield TCP estimates that lie in the shoulder of the dose response curve. However, for dose distributions that yield TCP estimates that lie on the steep part of the dose response curve or for inhomogeneous dose distributions having significant hot and/or cold regions, bystander effects may be important. Furthermore, the proposed model highlights a previously unexplored and potentially fruitful connection between the fields of statistical mechanics and tumor control probability/normal tissue complication probability modeling.

Convergence of Transition Probability Matrix in CLVMarkov Models

Science.gov (United States)

Permana, D.; Pasaribu, U. S.; Indratno, S. W.; Suprayogi, S.

2018-04-01

A transition probability matrix is an arrangement of transition probability from one states to another in a Markov chain model (MCM). One of interesting study on the MCM is its behavior for a long time in the future. The behavior is derived from one property of transition probabilty matrix for n steps. This term is called the convergence of the n-step transition matrix for n move to infinity. Mathematically, the convergence of the transition probability matrix is finding the limit of the transition matrix which is powered by n where n moves to infinity. The convergence form of the transition probability matrix is very interesting as it will bring the matrix to its stationary form. This form is useful for predicting the probability of transitions between states in the future. The method usually used to find the convergence of transition probability matrix is through the process of limiting the distribution. In this paper, the convergence of the transition probability matrix is searched using a simple concept of linear algebra that is by diagonalizing the matrix.This method has a higher level of complexity because it has to perform the process of diagonalization in its matrix. But this way has the advantage of obtaining a common form of power n of the transition probability matrix. This form is useful to see transition matrix before stationary. For example cases are taken from CLV model using MCM called Model of CLV-Markov. There are several models taken by its transition probability matrix to find its convergence form. The result is that the convergence of the matrix of transition probability through diagonalization has similarity with convergence with commonly used distribution of probability limiting method.

Comparing coefficients of nested nonlinear probability models

DEFF Research Database (Denmark)

Kohler, Ulrich; Karlson, Kristian Bernt; Holm, Anders

2011-01-01

In a series of recent articles, Karlson, Holm and Breen have developed a method for comparing the estimated coeffcients of two nested nonlinear probability models. This article describes this method and the user-written program khb that implements the method. The KHB-method is a general decomposi......In a series of recent articles, Karlson, Holm and Breen have developed a method for comparing the estimated coeffcients of two nested nonlinear probability models. This article describes this method and the user-written program khb that implements the method. The KHB-method is a general...... decomposition method that is unaffected by the rescaling or attenuation bias that arise in cross-model comparisons in nonlinear models. It recovers the degree to which a control variable, Z, mediates or explains the relationship between X and a latent outcome variable, Y*, underlying the nonlinear probability...

Predicting Cumulative Incidence Probability: Marginal and Cause-Specific Modelling

DEFF Research Database (Denmark)

Scheike, Thomas H.; Zhang, Mei-Jie

2005-01-01

cumulative incidence probability; cause-specific hazards; subdistribution hazard; binomial modelling......cumulative incidence probability; cause-specific hazards; subdistribution hazard; binomial modelling...

Two-slit experiment: quantum and classical probabilities

International Nuclear Information System (INIS)

Khrennikov, Andrei

2015-01-01

Inter-relation between quantum and classical probability models is one of the most fundamental problems of quantum foundations. Nowadays this problem also plays an important role in quantum technologies, in quantum cryptography and the theory of quantum random generators. In this letter, we compare the viewpoint of Richard Feynman that the behavior of quantum particles cannot be described by classical probability theory with the viewpoint that quantum–classical inter-relation is more complicated (cf, in particular, with the tomographic model of quantum mechanics developed in detail by Vladimir Man'ko). As a basic example, we consider the two-slit experiment, which played a crucial role in quantum foundational debates at the beginning of quantum mechanics (QM). In particular, its analysis led Niels Bohr to the formulation of the principle of complementarity. First, we demonstrate that in complete accordance with Feynman's viewpoint, the probabilities for the two-slit experiment have the non-Kolmogorovian structure, since they violate one of basic laws of classical probability theory, the law of total probability (the heart of the Bayesian analysis). However, then we show that these probabilities can be embedded in a natural way into the classical (Kolmogorov, 1933) probability model. To do this, one has to take into account the randomness of selection of different experimental contexts, the joint consideration of which led Feynman to a conclusion about the non-classicality of quantum probability. We compare this embedding of non-Kolmogorovian quantum probabilities into the Kolmogorov model with well-known embeddings of non-Euclidean geometries into Euclidean space (e.g., the Poincaré disk model for the Lobachvesky plane). (paper)

Dosimetric complication probability and acoustic analysis of vocal cord region in oropharyngeal carcinoma treated with voice-sparing intensity modulated radiotherapy

International Nuclear Information System (INIS)

Jain, S.; Gupta, T.; Agarwal, J.P.; Baccher, G.; Shrivastava, S.K.; Reenadevi; Master, J.

2008-01-01

Radiation to larynx has long been associated with speech and voice dysfunction. The objective is to study dosimetric parameters and complication probability of vocal cord region (VCR) and the effect of voice-sparing (VS) in the patients treated with intensity modulated radiotherapy (IMRT). The secondary objective is to describe the post-radiation acoustic voice characteristics and correlate them with the dosimetric parameters. (author)

Impact of target point deviations on control and complication probabilities in stereotactic radiosurgery of AVMs and metastases

International Nuclear Information System (INIS)

Treuer, Harald; Kocher, Martin; Hoevels, Moritz; Hunsche, Stefan; Luyken, Klaus; Maarouf, Mohammad; Voges, Juergen; Mueller, Rolf-Peter; Sturm, Volker

2006-01-01

Objective: Determination of the impact of inaccuracies in the determination and setup of the target point in stereotactic radiosurgery (SRS) on the expectable complication and control probabilities. Methods: Two randomized samples of patients with arteriovenous malformation (AVM) (n = 20) and with brain metastases (n = 20) treated with SRS were formed, and the probability for complete obliteration (COP) or complete remission (CRP), the size of the 10 Gy-volume in the brain tissue (VOI10), and the probability for radiation necrosis (NTCP) were calculated. The dose-effect relations for COP and CRP were fitted to clinical data. Target point deviations were simulated through random vectors and the resulting probabilities and volumes were calculated and compared with the values of the treatment plan. Results: The decrease of the relative value of the control probabilities at 1 mm target point deviation was up to 4% for AVMs and up to 10% for metastases. At 2 mm the median decrease was 5% for AVMs and 9% for metastases. The value for the target point deviation, at which COP and CRP decreased about 0.05 in 90% of the cases, was 1.3 mm. The increase of NTCP was maximally 0.0025 per mm target point deviation for AVMs and 0.0035/mm for metastases. The maximal increase of VOI10 was 0.7 cm 3 /mm target point deviation in both patient groups. Conclusions: The upper limit for tolerable target point deviations is at 1.3 mm. If this value cannot be achieved during the system test, a supplementary safety margin should be applied for the definition of the target volume. A better accuracy level is desirable, in order to ensure optimal chances for the success of the treatment. The target point precision is less important for the minimization of the probability of radiation necroses

Converting dose distributions into tumour control probability

International Nuclear Information System (INIS)

Nahum, A.E.

1996-01-01

The endpoints in radiotherapy that are truly of relevance are not dose distributions but the probability of local control, sometimes known as the Tumour Control Probability (TCP) and the Probability of Normal Tissue Complications (NTCP). A model for the estimation of TCP based on simple radiobiological considerations is described. It is shown that incorporation of inter-patient heterogeneity into the radiosensitivity parameter a through s a can result in a clinically realistic slope for the dose-response curve. The model is applied to inhomogeneous target dose distributions in order to demonstrate the relationship between dose uniformity and s a . The consequences of varying clonogenic density are also explored. Finally the model is applied to the target-volume DVHs for patients in a clinical trial of conformal pelvic radiotherapy; the effect of dose inhomogeneities on distributions of TCP are shown as well as the potential benefits of customizing the target dose according to normal-tissue DVHs. (author). 37 refs, 9 figs

Converting dose distributions into tumour control probability

Energy Technology Data Exchange (ETDEWEB)

Nahum, A E [The Royal Marsden Hospital, London (United Kingdom). Joint Dept. of Physics

1996-08-01

The endpoints in radiotherapy that are truly of relevance are not dose distributions but the probability of local control, sometimes known as the Tumour Control Probability (TCP) and the Probability of Normal Tissue Complications (NTCP). A model for the estimation of TCP based on simple radiobiological considerations is described. It is shown that incorporation of inter-patient heterogeneity into the radiosensitivity parameter a through s{sub a} can result in a clinically realistic slope for the dose-response curve. The model is applied to inhomogeneous target dose distributions in order to demonstrate the relationship between dose uniformity and s{sub a}. The consequences of varying clonogenic density are also explored. Finally the model is applied to the target-volume DVHs for patients in a clinical trial of conformal pelvic radiotherapy; the effect of dose inhomogeneities on distributions of TCP are shown as well as the potential benefits of customizing the target dose according to normal-tissue DVHs. (author). 37 refs, 9 figs.

Uncertainty the soul of modeling, probability & statistics

CERN Document Server

Briggs, William

2016-01-01

This book presents a philosophical approach to probability and probabilistic thinking, considering the underpinnings of probabilistic reasoning and modeling, which effectively underlie everything in data science. The ultimate goal is to call into question many standard tenets and lay the philosophical and probabilistic groundwork and infrastructure for statistical modeling. It is the first book devoted to the philosophy of data aimed at working scientists and calls for a new consideration in the practice of probability and statistics to eliminate what has been referred to as the "Cult of Statistical Significance". The book explains the philosophy of these ideas and not the mathematics, though there are a handful of mathematical examples. The topics are logically laid out, starting with basic philosophy as related to probability, statistics, and science, and stepping through the key probabilistic ideas and concepts, and ending with statistical models. Its jargon-free approach asserts that standard methods, suc...

Discovering Diabetes Complications: an Ontology Based Model.

Science.gov (United States)

Daghistani, Tahani; Shammari, Riyad Al; Razzak, Muhammad Imran

2015-12-01

Diabetes is a serious disease that spread in the world dramatically. The diabetes patient has an average of risk to experience complications. Take advantage of recorded information to build ontology as information technology solution will help to predict patients who have average of risk level with certain complication. It is helpful to search and present patient's history regarding different risk factors. Discovering diabetes complications could be useful to prevent or delay the complications. We designed ontology based model, using adult diabetes patients' data, to discover the rules of diabetes with its complications in disease to disease relationship. Various rules between different risk factors of diabetes Patients and certain complications generated. Furthermore, new complications (diseases) might be discovered as new finding of this study, discovering diabetes complications could be useful to prevent or delay the complications. The system can identify the patients who are suffering from certain risk factors such as high body mass index (obesity) and starting controlling and maintaining plan.

A quantum probability model of causal reasoning

Directory of Open Access Journals (Sweden)

Jennifer S Trueblood

2012-05-01

Full Text Available People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause with diagnostic judgments (i.e., the conditional probability of a cause given an effect. The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment.

Illustrating Probability through Roulette: A Spreadsheet Simulation Model

Directory of Open Access Journals (Sweden)

Kala Chand Seal

2005-11-01

Full Text Available Teaching probability can be challenging because the mathematical formulas often are too abstract and complex for the students to fully grasp the underlying meaning and effect of the concepts. Games can provide a way to address this issue. For example, the game of roulette can be an exciting application for teaching probability concepts. In this paper, we implement a model of roulette in a spreadsheet that can simulate outcomes of various betting strategies. The simulations can be analyzed to gain better insights into the corresponding probability structures. We use the model to simulate a particular betting strategy known as the bet-doubling, or Martingale, strategy. This strategy is quite popular and is often erroneously perceived as a winning strategy even though the probability analysis shows that such a perception is incorrect. The simulation allows us to present the true implications of such a strategy for a player with a limited betting budget and relate the results to the underlying theoretical probability structure. The overall validation of the model, its use for teaching, including its application to analyze other types of betting strategies are discussed.

Maximum parsimony, substitution model, and probability phylogenetic trees.

Science.gov (United States)

Weng, J F; Thomas, D A; Mareels, I

2011-01-01

The problem of inferring phylogenies (phylogenetic trees) is one of the main problems in computational biology. There are three main methods for inferring phylogenies-Maximum Parsimony (MP), Distance Matrix (DM) and Maximum Likelihood (ML), of which the MP method is the most well-studied and popular method. In the MP method the optimization criterion is the number of substitutions of the nucleotides computed by the differences in the investigated nucleotide sequences. However, the MP method is often criticized as it only counts the substitutions observable at the current time and all the unobservable substitutions that really occur in the evolutionary history are omitted. In order to take into account the unobservable substitutions, some substitution models have been established and they are now widely used in the DM and ML methods but these substitution models cannot be used within the classical MP method. Recently the authors proposed a probability representation model for phylogenetic trees and the reconstructed trees in this model are called probability phylogenetic trees. One of the advantages of the probability representation model is that it can include a substitution model to infer phylogenetic trees based on the MP principle. In this paper we explain how to use a substitution model in the reconstruction of probability phylogenetic trees and show the advantage of this approach with examples.

On the structure of the quantum-mechanical probability models

International Nuclear Information System (INIS)

Cufaro-Petroni, N.

1992-01-01

In this paper the role of the mathematical probability models in the classical and quantum physics in shortly analyzed. In particular the formal structure of the quantum probability spaces (QPS) is contrasted with the usual Kolmogorovian models of probability by putting in evidence the connections between this structure and the fundamental principles of the quantum mechanics. The fact that there is no unique Kolmogorovian model reproducing a QPS is recognized as one of the main reasons of the paradoxical behaviors pointed out in the quantum theory from its early days. 8 refs

Risk Probabilities

DEFF Research Database (Denmark)

Rojas-Nandayapa, Leonardo

Tail probabilities of sums of heavy-tailed random variables are of a major importance in various branches of Applied Probability, such as Risk Theory, Queueing Theory, Financial Management, and are subject to intense research nowadays. To understand their relevance one just needs to think...... analytic expression for the distribution function of a sum of random variables. The presence of heavy-tailed random variables complicates the problem even more. The objective of this dissertation is to provide better approximations by means of sharp asymptotic expressions and Monte Carlo estimators...

Multiple model cardinalized probability hypothesis density filter

Science.gov (United States)

Georgescu, Ramona; Willett, Peter

2011-09-01

The Probability Hypothesis Density (PHD) filter propagates the first-moment approximation to the multi-target Bayesian posterior distribution while the Cardinalized PHD (CPHD) filter propagates both the posterior likelihood of (an unlabeled) target state and the posterior probability mass function of the number of targets. Extensions of the PHD filter to the multiple model (MM) framework have been published and were implemented either with a Sequential Monte Carlo or a Gaussian Mixture approach. In this work, we introduce the multiple model version of the more elaborate CPHD filter. We present the derivation of the prediction and update steps of the MMCPHD particularized for the case of two target motion models and proceed to show that in the case of a single model, the new MMCPHD equations reduce to the original CPHD equations.

A COMPLICATED GRIEF INTERVENTION MODEL

African Journals Online (AJOL)

2010-07-29

Jul 29, 2010 ... work approach to therapy) in an attempt to develop a model for complicated grief intervention ..... way feels right for them, thus making them equal partners with .... This question points out the benefits of success and affords the.

Modeling experiments using quantum and Kolmogorov probability

International Nuclear Information System (INIS)

Hess, Karl

2008-01-01

Criteria are presented that permit a straightforward partition of experiments into sets that can be modeled using both quantum probability and the classical probability framework of Kolmogorov. These new criteria concentrate on the operational aspects of the experiments and lead beyond the commonly appreciated partition by relating experiments to commuting and non-commuting quantum operators as well as non-entangled and entangled wavefunctions. In other words the space of experiments that can be understood using classical probability is larger than usually assumed. This knowledge provides advantages for areas such as nanoscience and engineering or quantum computation.

Models for probability and statistical inference theory and applications

CERN Document Server

Stapleton, James H

2007-01-01

This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readersModels for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping.Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses mo...

Some simple applications of probability models to birth intervals

International Nuclear Information System (INIS)

Shrestha, G.

1987-07-01

An attempt has been made in this paper to apply some simple probability models to birth intervals under the assumption of constant fecundability and varying fecundability among women. The parameters of the probability models are estimated by using the method of moments and the method of maximum likelihood. (author). 9 refs, 2 tabs

Modeling the probability distribution of peak discharge for infiltrating hillslopes

Science.gov (United States)

Baiamonte, Giorgio; Singh, Vijay P.

2017-07-01

Hillslope response plays a fundamental role in the prediction of peak discharge at the basin outlet. The peak discharge for the critical duration of rainfall and its probability distribution are needed for designing urban infrastructure facilities. This study derives the probability distribution, denoted as GABS model, by coupling three models: (1) the Green-Ampt model for computing infiltration, (2) the kinematic wave model for computing discharge hydrograph from the hillslope, and (3) the intensity-duration-frequency (IDF) model for computing design rainfall intensity. The Hortonian mechanism for runoff generation is employed for computing the surface runoff hydrograph. Since the antecedent soil moisture condition (ASMC) significantly affects the rate of infiltration, its effect on the probability distribution of peak discharge is investigated. Application to a watershed in Sicily, Italy, shows that with the increase of probability, the expected effect of ASMC to increase the maximum discharge diminishes. Only for low values of probability, the critical duration of rainfall is influenced by ASMC, whereas its effect on the peak discharge seems to be less for any probability. For a set of parameters, the derived probability distribution of peak discharge seems to be fitted by the gamma distribution well. Finally, an application to a small watershed, with the aim to test the possibility to arrange in advance the rational runoff coefficient tables to be used for the rational method, and a comparison between peak discharges obtained by the GABS model with those measured in an experimental flume for a loamy-sand soil were carried out.

Statistical physics of pairwise probability models

DEFF Research Database (Denmark)

Roudi, Yasser; Aurell, Erik; Hertz, John

2009-01-01

(dansk abstrakt findes ikke) Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of  data......: knowledge of the means and correlations between pairs of elements in the system is sufficient. Not surprisingly, then, using pairwise models for studying neural data has been the focus of many studies in recent years. In this paper, we describe how tools from statistical physics can be employed for studying...

Probability of obliteration and management risk following gamma knife surgery for cerebral AVM

International Nuclear Information System (INIS)

Karlsson, B.; Lax, I.

1998-01-01

In order to define the optimal treatment for an AVM patient, the probability of cure and the management risk following the treatment must be estimated before the treatment. Here, Gamma Knife surgery has an advantage over microsurgery and embolization with it's reproducibility within the variability of the individual radiation sensitivity. Based on more than 2000 treatments, we have developed models to predict the probability for obliteration, the risk for radioinduced complications and the probability for a post treatment hemorrhage within the first two years following a Gamma Knife treatment. The factors determining the overall outcome are the absorbed dose in the target and the brain, the AVM volume and location and the age and clinical history of the patient. The probability for obliteration equals 35,69 * ln(D min )-39,66 and is AVM volume independent. The risk for radioinduced complications relates to the average dose in the 20 cm 3 tissue receiving the most radiation, and it is also related to the clinical history of the patient and the AVM location. Finally, the risk for post treatment hemorrhage increases with the age of the patient, and is higher for larger AVM. It decreases with increasing amount of radiation given, and it is independent of the clinical history of the patient. For retreatments, the model for prediction of obliteration is valid, but the risk for radioinduced complications is higher and the risk for post treatment hemorrhage lower as compared to following the first treatment. (author)

Idealized models of the joint probability distribution of wind speeds

Science.gov (United States)

Monahan, Adam H.

2018-05-01

The joint probability distribution of wind speeds at two separate locations in space or points in time completely characterizes the statistical dependence of these two quantities, providing more information than linear measures such as correlation. In this study, we consider two models of the joint distribution of wind speeds obtained from idealized models of the dependence structure of the horizontal wind velocity components. The bivariate Rice distribution follows from assuming that the wind components have Gaussian and isotropic fluctuations. The bivariate Weibull distribution arises from power law transformations of wind speeds corresponding to vector components with Gaussian, isotropic, mean-zero variability. Maximum likelihood estimates of these distributions are compared using wind speed data from the mid-troposphere, from different altitudes at the Cabauw tower in the Netherlands, and from scatterometer observations over the sea surface. While the bivariate Rice distribution is more flexible and can represent a broader class of dependence structures, the bivariate Weibull distribution is mathematically simpler and may be more convenient in many applications. The complexity of the mathematical expressions obtained for the joint distributions suggests that the development of explicit functional forms for multivariate speed distributions from distributions of the components will not be practical for more complicated dependence structure or more than two speed variables.

Probability Modeling and Thinking: What Can We Learn from Practice?

Science.gov (United States)

Pfannkuch, Maxine; Budgett, Stephanie; Fewster, Rachel; Fitch, Marie; Pattenwise, Simeon; Wild, Chris; Ziedins, Ilze

2016-01-01

Because new learning technologies are enabling students to build and explore probability models, we believe that there is a need to determine the big enduring ideas that underpin probabilistic thinking and modeling. By uncovering the elements of the thinking modes of expert users of probability models we aim to provide a base for the setting of…

Normal tissue complication probabilities correlated with late effects in the rectum after prostate conformal radiotherapy

International Nuclear Information System (INIS)

Dale, Einar; Olsen, Dag R.; Fossa, Sophie D.

1999-01-01

Purpose: Radiation therapy of deep-sited tumours will always result in normal tissue doses to some extent. The aim of this study was to calculate different risk estimates of late effects in the rectum for a group of cancer prostate patients treated with conformal radiation therapy (CRT) and correlate these estimates with the occurrences of late effects. Since the rectum is a hollow organ, several ways of generating dose-volume distributions over the organ are possible, and we wanted to investigate two of them. Methods and Materials: A mathematical model, known as the Lyman-Kutcher model, conventionally used to estimate normal tissue complication probabilities (NTCP) associated with radiation therapy, was applied to a material of 52 cancer prostate patients. The patients were treated with a four field box technique, with the rectum as organ at risk. Dose-volume histograms (DVH) were generated for the whole rectum (including the cavity) and of the rectum wall. One to two years after the treatment, the patients completed a questionnaire concerning bowel (rectum) related morbidity quantifying the extent of late effects. Results: A correlation analysis using Spearman's rank correlation coefficient, for NTCP values calculated from the DVHs and the patients' scores, gave correlation coefficients which were not statistically significant at the p max , of the whole rectum, correlated better to observed late toxicity than D max derived from histograms of the rectum wall. Correlation coefficients from 'high-dose' measures were larger than those calculated from the NTCP values. Accordingly, as the volume parameter of the Lyman-Kutcher model was reduced, raising the impact of small high-dose volumes on the NTCP values, the correlation between observed effects and NTCP values became significant at p < 0.01 level. Conclusions: 1) High-dose levels corresponding to small volume fractions of the cumulative dose-volume histograms were best correlated with the occurrences of late

Evaluation of nuclear power plant component failure probability and core damage probability using simplified PSA model

International Nuclear Information System (INIS)

Shimada, Yoshio

2000-01-01

It is anticipated that the change of frequency of surveillance tests, preventive maintenance or parts replacement of safety related components may cause the change of component failure probability and result in the change of core damage probability. It is also anticipated that the change is different depending on the initiating event frequency or the component types. This study assessed the change of core damage probability using simplified PSA model capable of calculating core damage probability in a short time period, which is developed by the US NRC to process accident sequence precursors, when various component's failure probability is changed between 0 and 1, or Japanese or American initiating event frequency data are used. As a result of the analysis, (1) It was clarified that frequency of surveillance test, preventive maintenance or parts replacement of motor driven pumps (high pressure injection pumps, residual heat removal pumps, auxiliary feedwater pumps) should be carefully changed, since the core damage probability's change is large, when the base failure probability changes toward increasing direction. (2) Core damage probability change is insensitive to surveillance test frequency change, since the core damage probability change is small, when motor operated valves and turbine driven auxiliary feed water pump failure probability changes around one figure. (3) Core damage probability change is small, when Japanese failure probability data are applied to emergency diesel generator, even if failure probability changes one figure from the base value. On the other hand, when American failure probability data is applied, core damage probability increase is large, even if failure probability changes toward increasing direction. Therefore, when Japanese failure probability data is applied, core damage probability change is insensitive to surveillance tests frequency change etc. (author)

On Probability Leakage

OpenAIRE

Briggs, William M.

2012-01-01

The probability leakage of model M with respect to evidence E is defined. Probability leakage is a kind of model error. It occurs when M implies that events $y$, which are impossible given E, have positive probability. Leakage does not imply model falsification. Models with probability leakage cannot be calibrated empirically. Regression models, which are ubiquitous in statistical practice, often evince probability leakage.

Applied probability models with optimization applications

CERN Document Server

Ross, Sheldon M

1992-01-01

Concise advanced-level introduction to stochastic processes that frequently arise in applied probability. Largely self-contained text covers Poisson process, renewal theory, Markov chains, inventory theory, Brownian motion and continuous time optimization models, much more. Problems and references at chapter ends. ""Excellent introduction."" - Journal of the American Statistical Association. Bibliography. 1970 edition.

Camera-Model Identification Using Markovian Transition Probability Matrix

Science.gov (United States)

Xu, Guanshuo; Gao, Shang; Shi, Yun Qing; Hu, Ruimin; Su, Wei

Detecting the (brands and) models of digital cameras from given digital images has become a popular research topic in the field of digital forensics. As most of images are JPEG compressed before they are output from cameras, we propose to use an effective image statistical model to characterize the difference JPEG 2-D arrays of Y and Cb components from the JPEG images taken by various camera models. Specifically, the transition probability matrices derived from four different directional Markov processes applied to the image difference JPEG 2-D arrays are used to identify statistical difference caused by image formation pipelines inside different camera models. All elements of the transition probability matrices, after a thresholding technique, are directly used as features for classification purpose. Multi-class support vector machines (SVM) are used as the classification tool. The effectiveness of our proposed statistical model is demonstrated by large-scale experimental results.

Discrete event simulation: Modeling simultaneous complications and outcomes

NARCIS (Netherlands)

Quik, E.H.; Feenstra, T.L.; Krabbe, P.F.M.

2012-01-01

OBJECTIVES: To present an effective and elegant model approach to deal with specific characteristics of complex modeling. METHODS: A discrete event simulation (DES) model with multiple complications and multiple outcomes that each can occur simultaneously was developed. In this DES model parameters,

Probability theory for 3-layer remote sensing radiative transfer model: univariate case.

Science.gov (United States)

Ben-David, Avishai; Davidson, Charles E

2012-04-23

A probability model for a 3-layer radiative transfer model (foreground layer, cloud layer, background layer, and an external source at the end of line of sight) has been developed. The 3-layer model is fundamentally important as the primary physical model in passive infrared remote sensing. The probability model is described by the Johnson family of distributions that are used as a fit for theoretically computed moments of the radiative transfer model. From the Johnson family we use the SU distribution that can address a wide range of skewness and kurtosis values (in addition to addressing the first two moments, mean and variance). In the limit, SU can also describe lognormal and normal distributions. With the probability model one can evaluate the potential for detecting a target (vapor cloud layer), the probability of observing thermal contrast, and evaluate performance (receiver operating characteristics curves) in clutter-noise limited scenarios. This is (to our knowledge) the first probability model for the 3-layer remote sensing geometry that treats all parameters as random variables and includes higher-order statistics. © 2012 Optical Society of America

Sampling, Probability Models and Statistical Reasoning Statistical

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 1; Issue 5. Sampling, Probability Models and Statistical Reasoning Statistical Inference. Mohan Delampady V R Padmawar. General Article Volume 1 Issue 5 May 1996 pp 49-58 ...

A probability model for the failure of pressure containing parts

International Nuclear Information System (INIS)

Thomas, H.M.

1978-01-01

The model provides a method of estimating the order of magnitude of the leakage failure probability of pressure containing parts. It is a fatigue based model which makes use of the statistics available for both specimens and vessels. Some novel concepts are introduced but essentially the model simply quantifies the obvious i.e. that failure probability increases with increases in stress levels, number of cycles, volume of material and volume of weld metal. A further model based on fracture mechanics estimates the catastrophic fraction of leakage failures. (author)

Gap probability - Measurements and models of a pecan orchard

Science.gov (United States)

Strahler, Alan H.; Li, Xiaowen; Moody, Aaron; Liu, YI

1992-01-01

Measurements and models are compared for gap probability in a pecan orchard. Measurements are based on panoramic photographs of 50* by 135 view angle made under the canopy looking upwards at regular positions along transects between orchard trees. The gap probability model is driven by geometric parameters at two levels-crown and leaf. Crown level parameters include the shape of the crown envelope and spacing of crowns; leaf level parameters include leaf size and shape, leaf area index, and leaf angle, all as functions of canopy position.

Developing a probability-based model of aquifer vulnerability in an agricultural region

Science.gov (United States)

Chen, Shih-Kai; Jang, Cheng-Shin; Peng, Yi-Huei

2013-04-01

SummaryHydrogeological settings of aquifers strongly influence the regional groundwater movement and pollution processes. Establishing a map of aquifer vulnerability is considerably critical for planning a scheme of groundwater quality protection. This study developed a novel probability-based DRASTIC model of aquifer vulnerability in the Choushui River alluvial fan, Taiwan, using indicator kriging and to determine various risk categories of contamination potentials based on estimated vulnerability indexes. Categories and ratings of six parameters in the probability-based DRASTIC model were probabilistically characterized according to the parameter classification methods of selecting a maximum estimation probability and calculating an expected value. Moreover, the probability-based estimation and assessment gave us an excellent insight into propagating the uncertainty of parameters due to limited observation data. To examine the prediction capacity of pollutants for the developed probability-based DRASTIC model, medium, high, and very high risk categories of contamination potentials were compared with observed nitrate-N exceeding 0.5 mg/L indicating the anthropogenic groundwater pollution. The analyzed results reveal that the developed probability-based DRASTIC model is capable of predicting high nitrate-N groundwater pollution and characterizing the parameter uncertainty via the probability estimation processes.

The Probability Model of Expectation Disconfirmation Process

Directory of Open Access Journals (Sweden)

Hui-Hsin HUANG

2015-06-01

Full Text Available This paper proposes a probability model to explore the dynamic process of customer’s satisfaction. Bases on expectation disconfirmation theory, the satisfaction is constructed with customer’s expectation before buying behavior and the perceived performance after purchase. The experiment method is designed to measure expectation disconfirmation effects and we also use the collection data to estimate the overall satisfaction and model calibration. The results show good fitness between the model and the real data. This model has application for business marketing areas in order to manage relationship satisfaction.

Method for Automatic Selection of Parameters in Normal Tissue Complication Probability Modeling

DEFF Research Database (Denmark)

Christophides, Damianos; Appelt, Ane L; Gusnanto, Arief

2018-01-01

by multicollinearity reduction using the variance inflation factor and genetic algorithm optimization to determine an ordinal logistic regression model that minimizes the Bayesian information criterion. The process was repeated 100 times, and the model with the minimum Bayesian information criterion was recorded...

Sampling, Probability Models and Statistical Reasoning -RE ...

Indian Academy of Sciences (India)

random sampling allows data to be modelled with the help of probability ... g based on different trials to get an estimate of the experimental error. ... research interests lie in the .... if e is indeed the true value of the proportion of defectives in the.

Probability theory

CERN Document Server

Dorogovtsev, A Ya; Skorokhod, A V; Silvestrov, D S; Skorokhod, A V

1997-01-01

This book of problems is intended for students in pure and applied mathematics. There are problems in traditional areas of probability theory and problems in the theory of stochastic processes, which has wide applications in the theory of automatic control, queuing and reliability theories, and in many other modern science and engineering fields. Answers to most of the problems are given, and the book provides hints and solutions for more complicated problems.

Knock probability estimation through an in-cylinder temperature model with exogenous noise

Science.gov (United States)

Bares, P.; Selmanaj, D.; Guardiola, C.; Onder, C.

2018-01-01

This paper presents a new knock model which combines a deterministic knock model based on the in-cylinder temperature and an exogenous noise disturbing this temperature. The autoignition of the end-gas is modelled by an Arrhenius-like function and the knock probability is estimated by propagating a virtual error probability distribution. Results show that the random nature of knock can be explained by uncertainties at the in-cylinder temperature estimation. The model only has one parameter for calibration and thus can be easily adapted online. In order to reduce the measurement uncertainties associated with the air mass flow sensor, the trapped mass is derived from the in-cylinder pressure resonance, which improves the knock probability estimation and reduces the number of sensors needed for the model. A four stroke SI engine was used for model validation. By varying the intake temperature, the engine speed, the injected fuel mass, and the spark advance, specific tests were conducted, which furnished data with various knock intensities and probabilities. The new model is able to predict the knock probability within a sufficient range at various operating conditions. The trapped mass obtained by the acoustical model was compared in steady conditions by using a fuel balance and a lambda sensor and differences below 1 % were found.

The extinction probability in systems randomly varying in time

Directory of Open Access Journals (Sweden)

Imre Pázsit

2017-09-01

Full Text Available The extinction probability of a branching process (a neutron chain in a multiplying medium is calculated for a system randomly varying in time. The evolution of the first two moments of such a process was calculated previously by the authors in a system randomly shifting between two states of different multiplication properties. The same model is used here for the investigation of the extinction probability. It is seen that the determination of the extinction probability is significantly more complicated than that of the moments, and it can only be achieved by pure numerical methods. The numerical results indicate that for systems fluctuating between two subcritical or two supercritical states, the extinction probability behaves as expected, but for systems fluctuating between a supercritical and a subcritical state, there is a crucial and unexpected deviation from the predicted behaviour. The results bear some significance not only for neutron chains in a multiplying medium, but also for the evolution of biological populations in a time-varying environment.

The Probability Heuristics Model of Syllogistic Reasoning.

Science.gov (United States)

Chater, Nick; Oaksford, Mike

1999-01-01

Proposes a probability heuristic model for syllogistic reasoning and confirms the rationality of this heuristic by an analysis of the probabilistic validity of syllogistic reasoning that treats logical inference as a limiting case of probabilistic inference. Meta-analysis and two experiments involving 40 adult participants and using generalized…

Probability and stochastic modeling

CERN Document Server

Rotar, Vladimir I

2012-01-01

Basic NotionsSample Space and EventsProbabilitiesCounting TechniquesIndependence and Conditional ProbabilityIndependenceConditioningThe Borel-Cantelli TheoremDiscrete Random VariablesRandom Variables and VectorsExpected ValueVariance and Other Moments. Inequalities for DeviationsSome Basic DistributionsConvergence of Random Variables. The Law of Large NumbersConditional ExpectationGenerating Functions. Branching Processes. Random Walk RevisitedBranching Processes Generating Functions Branching Processes Revisited More on Random WalkMarkov ChainsDefinitions and Examples. Probability Distributions of Markov ChainsThe First Step Analysis. Passage TimesVariables Defined on a Markov ChainErgodicity and Stationary DistributionsA Classification of States and ErgodicityContinuous Random VariablesContinuous DistributionsSome Basic Distributions Continuous Multivariate Distributions Sums of Independent Random Variables Conditional Distributions and ExpectationsDistributions in the General Case. SimulationDistribution F...

NASA Lewis Launch Collision Probability Model Developed and Analyzed

Science.gov (United States)

Bollenbacher, Gary; Guptill, James D

1999-01-01

There are nearly 10,000 tracked objects orbiting the earth. These objects encompass manned objects, active and decommissioned satellites, spent rocket bodies, and debris. They range from a few centimeters across to the size of the MIR space station. Anytime a new satellite is launched, the launch vehicle with its payload attached passes through an area of space in which these objects orbit. Although the population density of these objects is low, there always is a small but finite probability of collision between the launch vehicle and one or more of these space objects. Even though the probability of collision is very low, for some payloads even this small risk is unacceptable. To mitigate the small risk of collision associated with launching at an arbitrary time within the daily launch window, NASA performs a prelaunch mission assurance Collision Avoidance Analysis (or COLA). For the COLA of the Cassini spacecraft, the NASA Lewis Research Center conducted an in-house development and analysis of a model for launch collision probability. The model allows a minimum clearance criteria to be used with the COLA analysis to ensure an acceptably low probability of collision. If, for any given liftoff time, the nominal launch vehicle trajectory would pass a space object with less than the minimum required clearance, launch would not be attempted at that time. The model assumes that the nominal positions of the orbiting objects and of the launch vehicle can be predicted as a function of time, and therefore, that any tracked object that comes within close proximity of the launch vehicle can be identified. For any such pair, these nominal positions can be used to calculate a nominal miss distance. The actual miss distances may differ substantially from the nominal miss distance, due, in part, to the statistical uncertainty of the knowledge of the objects positions. The model further assumes that these position uncertainties can be described with position covariance matrices

Neutron transport by collision probability method in complicated geometries

International Nuclear Information System (INIS)

Constantin, Marin

2000-01-01

For the first flight collision probability (FFCP) method a rapidly increasing of the memory requirements and execution time with the number of discrete regions occurs. Generally, the use of the method is restricted at cell/supercell level. However, the amazing developments both in computer hardware and computer architecture allow a real extending of the problems' domain and a more detailed treatment of the geometry. Two ways are discussed into the paper: the direct design of new codes and the improving of the mainframe old versions. The author's experience is focused on the performances' improving of the 3D integral transport code PIJXYZ (from an old version to a modern one) and on the design and developing of the 2D transport code CP 2 D in the last years. In the first case an optimization process have been performed before the parallelization. In the second a modular design and the newest techniques (factorization of the geometry, the macrobands method, the mobile set of chords, the automatic calculation of the integration error, optimal algorithms for the innermost programming level, the mixed method for tracking process and CPs calculation, etc.) were adopted. In both cases the parallelization uses a PCs network system. Some short examples for CP 2 D and PIJXYZ calculation are presented: reactivity void effect in typical CANDU cells using a multistratified coolant model, a problem of some adjacent fuel assemblies, CANDU reactivity devices 3D simulation. (author)

Predictive Value of C-Reactive Protein for Major Complications after Major Abdominal Surgery: A Systematic Review and Pooled-Analysis.

Directory of Open Access Journals (Sweden)

Jennifer Straatman

Full Text Available Early diagnosis and treatment of complications after major abdominal surgery can decrease associated morbidity and mortality. Postoperative CRP levels have shown a strong correlation with complications. Aim of this systematic review and pooled-analysis was to assess postoperative values of CRP as a marker for major complications and construct a prediction model.A systematic review was performed for CRP levels as a predictor for complications after major abdominal surgery (MAS. Raw data was obtained from seven studies, including 1427 patients. A logit regression model assessed the probability of major complications as a function of CRP levels on the third postoperative day. Two practical cut-offs are proposed: an optimal cut-off for safe discharge in a fast track protocol and another for early identification of patients with increased risk for major complications.A prediction model was calculated for major complications as a function of CRP levels on the third postoperative day. Based on the model several cut-offs for CRP are proposed. For instance, a two cut-off system may be applied, consisting of a safe discharge criterion with CRP levels below 75 mg/L, with a negative predictive value of 97.2%. A second cut-off is set at 215 mg/L (probability 20% and serves as a predictor of complications, indicating additional CT-scan imaging.The present study provides insight in the interpretation of CRP levels after major abdominal surgery, proposing a prediction model for major complications as a function of CRP on postoperative day 3. Cut-offs for CRP may be implemented for safe early-discharge in a fast-track protocol and, secondly as a threshold for additional examinations, such as CT-scan imaging, even in absence of clinical signs, to confirm or exclude major complications. The prediction model allows for setting a cut-off at the discretion of individual surgeons or surgical departments.

Predicting medical complications after spine surgery: a validated model using a prospective surgical registry.

Science.gov (United States)

Lee, Michael J; Cizik, Amy M; Hamilton, Deven; Chapman, Jens R

2014-02-01

The possibility and likelihood of a postoperative medical complication after spine surgery undoubtedly play a major role in the decision making of the surgeon and patient alike. Although prior study has determined relative risk and odds ratio values to quantify risk factors, these values may be difficult to translate to the patient during counseling of surgical options. Ideally, a model that predicts absolute risk of medical complication, rather than relative risk or odds ratio values, would greatly enhance the discussion of safety of spine surgery. To date, there is no risk stratification model that specifically predicts the risk of medical complication. The purpose of this study was to create and validate a predictive model for the risk of medical complication during and after spine surgery. Statistical analysis using a prospective surgical spine registry that recorded extensive demographic, surgical, and complication data. Outcomes examined are medical complications that were specifically defined a priori. This analysis is a continuation of statistical analysis of our previously published report. Using a prospectively collected surgical registry of more than 1,476 patients with extensive demographic, comorbidity, surgical, and complication detail recorded for 2 years after surgery, we previously identified several risk factor for medical complications. Using the beta coefficients from those log binomial regression analyses, we created a model to predict the occurrence of medical complication after spine surgery. We split our data into two subsets for internal and cross-validation of our model. We created two predictive models: one predicting the occurrence of any medical complication and the other predicting the occurrence of a major medical complication. The final predictive model for any medical complications had a receiver operator curve characteristic of 0.76, considered to be a fair measure. The final predictive model for any major medical complications had

Probability model for analyzing fire management alternatives: theory and structure

Science.gov (United States)

Frederick W. Bratten

1982-01-01

A theoretical probability model has been developed for analyzing program alternatives in fire management. It includes submodels or modules for predicting probabilities of fire behavior, fire occurrence, fire suppression, effects of fire on land resources, and financial effects of fire. Generalized "fire management situations" are used to represent actual fire...

Fixation probability in a two-locus intersexual selection model.

Science.gov (United States)

Durand, Guillermo; Lessard, Sabin

2016-06-01

We study a two-locus model of intersexual selection in a finite haploid population reproducing according to a discrete-time Moran model with a trait locus expressed in males and a preference locus expressed in females. We show that the probability of ultimate fixation of a single mutant allele for a male ornament introduced at random at the trait locus given any initial frequency state at the preference locus is increased by weak intersexual selection and recombination, weak or strong. Moreover, this probability exceeds the initial frequency of the mutant allele even in the case of a costly male ornament if intersexual selection is not too weak. On the other hand, the probability of ultimate fixation of a single mutant allele for a female preference towards a male ornament introduced at random at the preference locus is increased by weak intersexual selection and weak recombination if the female preference is not costly, and is strong enough in the case of a costly male ornament. The analysis relies on an extension of the ancestral recombination-selection graph for samples of haplotypes to take into account events of intersexual selection, while the symbolic calculation of the fixation probabilities is made possible in a reasonable time by an optimizing algorithm. Copyright © 2016 Elsevier Inc. All rights reserved.

The collision probability modules of WIMS-E

International Nuclear Information System (INIS)

Roth, M.J.

1985-04-01

This report describes how flat source first flight collision probabilities are calculated and used in the WIMS-E modular program. It includes a description of the input to the modules W-FLU, W-THES, W-PIP, W-PERS and W-MERGE. Input to other collision probability modules are described in separate reports. WIMS-E is capable of calculating collision probabilities in a wide variety of geometries, some of them quite complicated. It can also use them for a variety of purposes. (author)

Evaluation of high myopia complications prevention program in university freshmen.

Science.gov (United States)

Tseng, Gow-Lieng; Chen, Cheng-Yu

2016-10-01

High myopia is a global eye health problem because of its high incidence of sight-threatening complications. Due to the role of awareness, self-examination, and preventive behavior in prevention of morbidity of high myopia complications, promoting knowledge, capabilities, and attitude of high myopic personnel are required in this regard.In this quasi-experiment study, 31 freshmen with high myopia in a national university were enrolled in 2014. The data were collected by validated and reliable questionnaire based on health belief model (HBM) and self-efficacy theory. The intervention program consisted of 1 educational session lasting 150 minutes by lecturing of high myopia complications, virtual reality experiencing, similarity modeling, and quibbling a film made on high myopia complications preventive concepts.Implementing the educational program showed immediate effect in knowledge, perceived susceptibility, perceived severity, self-efficacy, and preventive behavior intention. While 6 weeks after the educational program, significant increases were observed in cues to action, self-efficacy, and preventive behavior intention.This article provided that, after a single session, there was positive improvement in high myopia complication prevention behavior intention among participants. These positive effects confirmed the efficacy of the education program and will probably induce behavior change.

Estimation and asymptotic theory for transition probabilities in Markov Renewal Multi–state models

NARCIS (Netherlands)

Spitoni, C.; Verduijn, M.; Putter, H.

2012-01-01

In this paper we discuss estimation of transition probabilities for semi–Markov multi–state models. Non–parametric and semi–parametric estimators of the transition probabilities for a large class of models (forward going models) are proposed. Large sample theory is derived using the functional

Using multinomial and imprecise probability for non-parametric modelling of rainfall in Manizales (Colombia

Directory of Open Access Journals (Sweden)

Ibsen Chivatá Cárdenas

2008-05-01

Full Text Available This article presents a rainfall model constructed by applying non-parametric modelling and imprecise probabilities; these tools were used because there was not enough homogeneous information in the study area. The area’s hydro-logical information regarding rainfall was scarce and existing hydrological time series were not uniform. A distributed extended rainfall model was constructed from so-called probability boxes (p-boxes, multinomial probability distribu-tion and confidence intervals (a friendly algorithm was constructed for non-parametric modelling by combining the last two tools. This model confirmed the high level of uncertainty involved in local rainfall modelling. Uncertainty en-compassed the whole range (domain of probability values thereby showing the severe limitations on information, leading to the conclusion that a detailed estimation of probability would lead to significant error. Nevertheless, rele-vant information was extracted; it was estimated that maximum daily rainfall threshold (70 mm would be surpassed at least once every three years and the magnitude of uncertainty affecting hydrological parameter estimation. This paper’s conclusions may be of interest to non-parametric modellers and decisions-makers as such modelling and imprecise probability represents an alternative for hydrological variable assessment and maybe an obligatory proce-dure in the future. Its potential lies in treating scarce information and represents a robust modelling strategy for non-seasonal stochastic modelling conditions

Statistical physics of pairwise probability models

Directory of Open Access Journals (Sweden)

Yasser Roudi

2009-11-01

Full Text Available Statistical models for describing the probability distribution over the states of biological systems are commonly used for dimensional reduction. Among these models, pairwise models are very attractive in part because they can be fit using a reasonable amount of data: knowledge of the means and correlations between pairs of elements in the system is sufficient. Not surprisingly, then, using pairwise models for studying neural data has been the focus of many studies in recent years. In this paper, we describe how tools from statistical physics can be employed for studying and using pairwise models. We build on our previous work on the subject and study the relation between different methods for fitting these models and evaluating their quality. In particular, using data from simulated cortical networks we study how the quality of various approximate methods for inferring the parameters in a pairwise model depends on the time bin chosen for binning the data. We also study the effect of the size of the time bin on the model quality itself, again using simulated data. We show that using finer time bins increases the quality of the pairwise model. We offer new ways of deriving the expressions reported in our previous work for assessing the quality of pairwise models.

Chemo-IMRT of Oropharyngeal Cancer Aiming to Reduce Dysphagia: Swallowing Organs Late Complication Probabilities and Dosimetric Correlates

International Nuclear Information System (INIS)

Eisbruch, Avraham; Kim, Hyungjin M.; Feng, Felix Y.; Lyden, Teresa H.; Haxer, Marc J.; Feng, Mary; Worden, Frank P.; Bradford, Carol R.; Prince, Mark E.; Moyer, Jeffrey S.; Wolf, Gregory T.; Chepeha, Douglas B.; Ten Haken, Randall K.

2011-01-01

Purpose: Assess dosimetric correlates of long-term dysphagia after chemo-intensity-modulated radiotherapy (IMRT) of oropharyngeal cancer (OPC) sparing parts of the swallowing organs. Patients and Methods: Prospective longitudinal study: weekly chemotherapy concurrent with IMRT for Stages III/IV OPC, aiming to reduce dysphagia by sparing noninvolved parts of swallowing-related organs: pharyngeal constrictors (PC), glottic and supraglottic larynx (GSL), and esophagus, as well as oral cavity and major salivary glands. Dysphagia outcomes included patient-reported Swallowing and Eating Domain scores, Observer-based (CTCAEv.2) dysphagia, and videofluoroscopy (VF), before and periodically after therapy through 2 years. Relationships between dosimetric factors and worsening (from baseline) of dysphagia through 2 years were assessed by linear mixed-effects model. Results: Seventy-three patients participated. Observer-based dysphagia was not modeled because at >6 months there were only four Grade ≥2 cases (one of whom was feeding-tube dependent). PC, GSL, and esophagus mean doses, as well as their partial volume doses (V D s), were each significantly correlated with all dysphagia outcomes. However, the V D s for each organ intercorrelated and also highly correlated with the mean doses, leaving only mean doses significant. Mean doses to each of the parts of the PCs (superior, middle, and inferior) were also significantly correlated with all dysphagia measures, with superior PCs demonstrating highest correlations. For VF-based strictures, most significant predictor was esophageal mean doses (48±17 Gy in patients with, vs 27±12 in patients without strictures, p = 0.004). Normal tissue complication probabilities (NTCPs) increased moderately with mean doses without any threshold. For increased VF-based aspirations or worsened VF summary scores, toxic doses (TDs) 50 and TD 25 were 63 Gy and 56 Gy for PC, and 56 Gy and 39 Gy for GSL, respectively. For both PC and GSL, patient

A stochastic-bayesian model for the fracture probability of PWR pressure vessels

Energy Technology Data Exchange (ETDEWEB)

Francisco, Alexandre S.; Duran, Jorge Alberto R., E-mail: afrancisco@metal.eeimvr.uff.br, E-mail: duran@metal.eeimvr.uff.br [Universidade Federal Fluminense (UFF), Volta Redonda, RJ (Brazil). Dept. de Engenharia Mecanica

2013-07-01

Fracture probability of pressure vessels containing cracks can be obtained by methodologies of easy understanding, which require a deterministic treatment, complemented by statistical methods. However, more accurate results are required, methodologies need to be better formulated. This paper presents a new methodology to address this problem. First, a more rigorous methodology is obtained by means of the relationship of probability distributions that model crack incidence and nondestructive inspection efficiency using the Bayes' theorem. The result is an updated crack incidence distribution. Further, the accuracy of the methodology is improved by using a stochastic model for the crack growth. The stochastic model incorporates the statistical variability of the crack growth process, combining the stochastic theory with experimental data. Stochastic differential equations are derived by the randomization of empirical equations. From the solution of this equation, a distribution function related to the crack growth is derived. The fracture probability using both probability distribution functions is in agreement with theory, and presents realistic value for pressure vessels. (author)

A stochastic-bayesian model for the fracture probability of PWR pressure vessels

International Nuclear Information System (INIS)

Francisco, Alexandre S.; Duran, Jorge Alberto R.

2013-01-01

Fracture probability of pressure vessels containing cracks can be obtained by methodologies of easy understanding, which require a deterministic treatment, complemented by statistical methods. However, more accurate results are required, methodologies need to be better formulated. This paper presents a new methodology to address this problem. First, a more rigorous methodology is obtained by means of the relationship of probability distributions that model crack incidence and nondestructive inspection efficiency using the Bayes' theorem. The result is an updated crack incidence distribution. Further, the accuracy of the methodology is improved by using a stochastic model for the crack growth. The stochastic model incorporates the statistical variability of the crack growth process, combining the stochastic theory with experimental data. Stochastic differential equations are derived by the randomization of empirical equations. From the solution of this equation, a distribution function related to the crack growth is derived. The fracture probability using both probability distribution functions is in agreement with theory, and presents realistic value for pressure vessels. (author)

Scaling Qualitative Probability

OpenAIRE

Burgin, Mark

2017-01-01

There are different approaches to qualitative probability, which includes subjective probability. We developed a representation of qualitative probability based on relational systems, which allows modeling uncertainty by probability structures and is more coherent than existing approaches. This setting makes it possible proving that any comparative probability is induced by some probability structure (Theorem 2.1), that classical probability is a probability structure (Theorem 2.2) and that i...

Probabilistic Inference: Task Dependency and Individual Differences of Probability Weighting Revealed by Hierarchical Bayesian Modeling.

Science.gov (United States)

Boos, Moritz; Seer, Caroline; Lange, Florian; Kopp, Bruno

2016-01-01

Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modeling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities) by two (likelihoods) design. Five computational models of cognitive processes were compared with the observed behavior. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted) S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model's success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modeling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modeling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

Statistical models based on conditional probability distributions

International Nuclear Information System (INIS)

Narayanan, R.S.

1991-10-01

We present a formulation of statistical mechanics models based on conditional probability distribution rather than a Hamiltonian. We show that it is possible to realize critical phenomena through this procedure. Closely linked with this formulation is a Monte Carlo algorithm, in which a configuration generated is guaranteed to be statistically independent from any other configuration for all values of the parameters, in particular near the critical point. (orig.)

Interpretations of probability

CERN Document Server

Khrennikov, Andrei

2009-01-01

This is the first fundamental book devoted to non-Kolmogorov probability models. It provides a mathematical theory of negative probabilities, with numerous applications to quantum physics, information theory, complexity, biology and psychology. The book also presents an interesting model of cognitive information reality with flows of information probabilities, describing the process of thinking, social, and psychological phenomena.

Ruin probability of the renewal model with risky investment and large claims

Institute of Scientific and Technical Information of China (English)

2009-01-01

The ruin probability of the renewal risk model with investment strategy for a capital market index is investigated in this paper.For claim sizes with common distribution of extended regular variation,we study the asymptotic behaviour of the ruin probability.As a corollary,we establish a simple asymptotic formula for the ruin probability for the case of Pareto-like claims.

Review of Literature for Model Assisted Probability of Detection

Energy Technology Data Exchange (ETDEWEB)

Meyer, Ryan M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Crawford, Susan L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lareau, John P. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Anderson, Michael T. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

2014-09-30

This is a draft technical letter report for NRC client documenting a literature review of model assisted probability of detection (MAPOD) for potential application to nuclear power plant components for improvement of field NDE performance estimations.

Interpretation of the results of statistical measurements. [search for basic probability model

Science.gov (United States)

Olshevskiy, V. V.

1973-01-01

For random processes, the calculated probability characteristic, and the measured statistical estimate are used in a quality functional, which defines the difference between the two functions. Based on the assumption that the statistical measurement procedure is organized so that the parameters for a selected model are optimized, it is shown that the interpretation of experimental research is a search for a basic probability model.

Probabilistic inference: Task dependency and individual differences of probability weighting revealed by hierarchical Bayesian modelling

Directory of Open Access Journals (Sweden)

Moritz eBoos

2016-05-01

Full Text Available Cognitive determinants of probabilistic inference were examined using hierarchical Bayesian modelling techniques. A classic urn-ball paradigm served as experimental strategy, involving a factorial two (prior probabilities by two (likelihoods design. Five computational models of cognitive processes were compared with the observed behaviour. Parameter-free Bayesian posterior probabilities and parameter-free base rate neglect provided inadequate models of probabilistic inference. The introduction of distorted subjective probabilities yielded more robust and generalizable results. A general class of (inverted S-shaped probability weighting functions had been proposed; however, the possibility of large differences in probability distortions not only across experimental conditions, but also across individuals, seems critical for the model’s success. It also seems advantageous to consider individual differences in parameters of probability weighting as being sampled from weakly informative prior distributions of individual parameter values. Thus, the results from hierarchical Bayesian modelling converge with previous results in revealing that probability weighting parameters show considerable task dependency and individual differences. Methodologically, this work exemplifies the usefulness of hierarchical Bayesian modelling techniques for cognitive psychology. Theoretically, human probabilistic inference might be best described as the application of individualized strategic policies for Bayesian belief revision.

Computation of Probabilities in Causal Models of History of Science

Directory of Open Access Journals (Sweden)

Osvaldo Pessoa Jr.

2006-12-01

Full Text Available : The aim of this paper is to investigate the ascription of probabilities in a causal model of an episode in the history of science. The aim of such a quantitative approach is to allow the implementation of the causal model in a computer, to run simulations. As an example, we look at the beginning of the science of magnetism, “explaining” — in a probabilistic way, in terms of a single causal model — why the field advanced in China but not in Europe (the difference is due to different prior probabilities of certain cultural manifestations. Given the number of years between the occurrences of two causally connected advances X and Y, one proposes a criterion for stipulating the value pY=X of the conditional probability of an advance Y occurring, given X. Next, one must assume a specific form for the cumulative probability function pY=X(t, which we take to be the time integral of an exponential distribution function, as is done in physics of radioactive decay. Rules for calculating the cumulative functions for more than two events are mentioned, involving composition, disjunction and conjunction of causes. We also consider the problems involved in supposing that the appearance of events in time follows an exponential distribution, which are a consequence of the fact that a composition of causes does not follow an exponential distribution, but a “hypoexponential” one. We suggest that a gamma distribution function might more adequately represent the appearance of advances.

Normal tissue complication probability: Does simultaneous integrated boost intensity-modulated radiotherapy score over other techniques in treatment of prostate adenocarcinoma

Directory of Open Access Journals (Sweden)

Jothy Basu K

2009-01-01

Full Text Available Aim: The main objective of this study was to analyze the radiobiological effect of different treatment strategies on high-risk prostate adenocarcinoma. Materials and Methods: Ten cases of high-risk prostate adenocarcinoma were selected for this dosimetric study. Four different treatment strategies used for treating prostate cancer were compared. Conventional four-field box technique covering prostate and nodal volumes followed by three-field conformal boost (3D + 3DCRT, four-field box technique followed by intensity-modulated radiotherapy (IMRT boost (3D + IMRT, IMRT followed by IMRT boost (IMRT + IMRT, and simultaneous integrated boost IMRT (SIBIMRT were compared in terms of tumor control probability (TCP and normal tissue complication probability (NTCP. The dose prescription except for SIBIMRT was 45 Gy in 25 fractions for the prostate and nodal volumes in the initial phase and 27 Gy in 15 fractions for the prostate in the boost phase. For SIBIMRT, equivalent doses were calculated using biologically equivalent dose assuming the α/β ratio of 1.5 Gy with a dose prescription of 60.75 Gy for the gross tumor volume (GTV and 45 Gy for the clinical target volume in 25 fractions. IMRT plans were made with 15-MV equispaced seven coplanar fields. NTCP was calculated using the Lyman-Kutcher-Burman (LKB model. Results: An NTCP of 10.7 ± 0.99%, 8.36 ± 0.66%, 6.72 ± 0.85%, and 1.45 ± 0.11% for the bladder and 14.9 ± 0.99%, 14.04 ± 0.66%, 11.38 ± 0.85%, 5.12 ± 0.11% for the rectum was seen with 3D + 3DCRT, 3D + IMRT, IMRT + IMRT, and SIBIMRT respectively. Conclusions: SIBIMRT had the least NTCP over all other strategies with a reduced treatment time (3 weeks less. It should be the technique of choice for dose escalation in prostate carcinoma.

Reach/frequency for printed media: Personal probabilities or models

DEFF Research Database (Denmark)

Mortensen, Peter Stendahl

2000-01-01

The author evaluates two different ways of estimating reach and frequency of plans for printed media. The first assigns reading probabilities to groups of respondents and calculates reach and frequency by simulation. the second estimates parameters to a model for reach/frequency. It is concluded ...... and estiamtes from such models are shown to be closer to panel data. the problem, however, is to get valid input for such models from readership surveys. Means for this are discussed....

A formalism to generate probability distributions for performance-assessment modeling

International Nuclear Information System (INIS)

Kaplan, P.G.

1990-01-01

A formalism is presented for generating probability distributions of parameters used in performance-assessment modeling. The formalism is used when data are either sparse or nonexistent. The appropriate distribution is a function of the known or estimated constraints and is chosen to maximize a quantity known as Shannon's informational entropy. The formalism is applied to a parameter used in performance-assessment modeling. The functional form of the model that defines the parameter, data from the actual field site, and natural analog data are analyzed to estimate the constraints. A beta probability distribution of the example parameter is generated after finding four constraints. As an example of how the formalism is applied to the site characterization studies of Yucca Mountain, the distribution is generated for an input parameter in a performance-assessment model currently used to estimate compliance with disposal of high-level radioactive waste in geologic repositories, 10 CFR 60.113(a)(2), commonly known as the ground water travel time criterion. 8 refs., 2 figs

The effect of 6 and 15 MV on intensity-modulated radiation therapy prostate cancer treatment: plan evaluation, tumour control probability and normal tissue complication probability analysis, and the theoretical risk of secondary induced malignancies

Science.gov (United States)

Hussein, M; Aldridge, S; Guerrero Urbano, T; Nisbet, A

2012-01-01

Objective The aim of this study was to investigate the effect of 6 and 15-MV photon energies on intensity-modulated radiation therapy (IMRT) prostate cancer treatment plan outcome and to compare the theoretical risks of secondary induced malignancies. Methods Separate prostate cancer IMRT plans were prepared for 6 and 15-MV beams. Organ-equivalent doses were obtained through thermoluminescent dosemeter measurements in an anthropomorphic Aldersen radiation therapy human phantom. The neutron dose contribution at 15 MV was measured using polyallyl-diglycol-carbonate neutron track etch detectors. Risk coefficients from the International Commission on Radiological Protection Report 103 were used to compare the risk of fatal secondary induced malignancies in out-of-field organs and tissues for 6 and 15 MV. For the bladder and the rectum, a comparative evaluation of the risk using three separate models was carried out. Dose–volume parameters for the rectum, bladder and prostate planning target volume were evaluated, as well as normal tissue complication probability (NTCP) and tumour control probability calculations. Results There is a small increased theoretical risk of developing a fatal cancer from 6 MV compared with 15 MV, taking into account all the organs. Dose–volume parameters for the rectum and bladder show that 15 MV results in better volume sparing in the regions below 70 Gy, but the volume exposed increases slightly beyond this in comparison with 6 MV, resulting in a higher NTCP for the rectum of 3.6% vs 3.0% (p=0.166). Conclusion The choice to treat using IMRT at 15 MV should not be excluded, but should be based on risk vs benefit while considering the age and life expectancy of the patient together with the relative risk of radiation-induced cancer and NTCPs. PMID:22010028

Correlates of time to microvascular complications among diabetes ...

African Journals Online (AJOL)

Socio-demographic and clinical factors have been known to affect the time to microvascular complications and survival probabilities of diabetes mellitus patients. The objective of this study was to identify risk factors and estimate average survival times for the time to the development of microvascular complications of ...

Probability Distribution and Deviation Information Fusion Driven Support Vector Regression Model and Its Application

Directory of Open Access Journals (Sweden)

Changhao Fan

2017-01-01

Full Text Available In modeling, only information from the deviation between the output of the support vector regression (SVR model and the training sample is considered, whereas the other prior information of the training sample, such as probability distribution information, is ignored. Probabilistic distribution information describes the overall distribution of sample data in a training sample that contains different degrees of noise and potential outliers, as well as helping develop a high-accuracy model. To mine and use the probability distribution information of a training sample, a new support vector regression model that incorporates probability distribution information weight SVR (PDISVR is proposed. In the PDISVR model, the probability distribution of each sample is considered as the weight and is then introduced into the error coefficient and slack variables of SVR. Thus, the deviation and probability distribution information of the training sample are both used in the PDISVR model to eliminate the influence of noise and outliers in the training sample and to improve predictive performance. Furthermore, examples with different degrees of noise were employed to demonstrate the performance of PDISVR, which was then compared with those of three SVR-based methods. The results showed that PDISVR performs better than the three other methods.

Modeling the radiation transfer of discontinuous canopies: results for gap probability and single-scattering contribution

Science.gov (United States)

Zhao, Feng; Zou, Kai; Shang, Hong; Ji, Zheng; Zhao, Huijie; Huang, Wenjiang; Li, Cunjun

2010-10-01

In this paper we present an analytical model for the computation of radiation transfer of discontinuous vegetation canopies. Some initial results of gap probability and bidirectional gap probability of discontinuous vegetation canopies, which are important parameters determining the radiative environment of the canopies, are given and compared with a 3- D computer simulation model. In the model, negative exponential attenuation of light within individual plant canopies is assumed. Then the computation of gap probability is resolved by determining the entry points and exiting points of the ray with the individual plants via their equations in space. For the bidirectional gap probability, which determines the single-scattering contribution of the canopy, a gap statistical analysis based model was adopted to correct the dependence of gap probabilities for both solar and viewing directions. The model incorporates the structural characteristics, such as plant sizes, leaf size, row spacing, foliage density, planting density, leaf inclination distribution. Available experimental data are inadequate for a complete validation of the model. So it was evaluated with a three dimensional computer simulation model for 3D vegetative scenes, which shows good agreement between these two models' results. This model should be useful to the quantification of light interception and the modeling of bidirectional reflectance distributions of discontinuous canopies.

Assigning probability distributions to input parameters of performance assessment models

Energy Technology Data Exchange (ETDEWEB)

Mishra, Srikanta [INTERA Inc., Austin, TX (United States)

2002-02-01

This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available.

Assigning probability distributions to input parameters of performance assessment models

International Nuclear Information System (INIS)

Mishra, Srikanta

2002-02-01

This study presents an overview of various approaches for assigning probability distributions to input parameters and/or future states of performance assessment models. Specifically,three broad approaches are discussed for developing input distributions: (a) fitting continuous distributions to data, (b) subjective assessment of probabilities, and (c) Bayesian updating of prior knowledge based on new information. The report begins with a summary of the nature of data and distributions, followed by a discussion of several common theoretical parametric models for characterizing distributions. Next, various techniques are presented for fitting continuous distributions to data. These include probability plotting, method of moments, maximum likelihood estimation and nonlinear least squares analysis. The techniques are demonstrated using data from a recent performance assessment study for the Yucca Mountain project. Goodness of fit techniques are also discussed, followed by an overview of how distribution fitting is accomplished in commercial software packages. The issue of subjective assessment of probabilities is dealt with in terms of the maximum entropy distribution selection approach, as well as some common rules for codifying informal expert judgment. Formal expert elicitation protocols are discussed next, and are based primarily on the guidance provided by the US NRC. The Bayesian framework for updating prior distributions (beliefs) when new information becomes available is discussed. A simple numerical approach is presented for facilitating practical applications of the Bayes theorem. Finally, a systematic framework for assigning distributions is presented: (a) for the situation where enough data are available to define an empirical CDF or fit a parametric model to the data, and (b) to deal with the situation where only a limited amount of information is available

Toward a generalized probability theory: conditional probabilities

International Nuclear Information System (INIS)

Cassinelli, G.

1979-01-01

The main mathematical object of interest in the quantum logic approach to the foundations of quantum mechanics is the orthomodular lattice and a set of probability measures, or states, defined by the lattice. This mathematical structure is studied per se, independently from the intuitive or physical motivation of its definition, as a generalized probability theory. It is thought that the building-up of such a probability theory could eventually throw light on the mathematical structure of Hilbert-space quantum mechanics as a particular concrete model of the generalized theory. (Auth.)

Neuromuscular complications of thyrotoxicosis.

Science.gov (United States)

Kung, Annie W C

2007-11-01

Thyroid hormones exert multiple effects on the neuromuscular system and the brain, with the most important being their role in stimulating the development and differentiation of the neuromuscular system and brain in foetal and neonatal life. In the presence of hyperthyroidism, muscular and neurological symptoms may be the presenting clinical features of the disease. The frequency and severity of neuromuscular complications vary considerably and are probably related to the degree of hyperthyroidism, although in some patients the neuromuscular dysfunction is caused by associated disorders rather than by hyperthyroidism per se. This update focuses on the most common neurological and muscular disorders that occur in patients with thyrotoxicosis. It is beyond the scope of this paper to discuss thyroid eye disease and cardiac complications, in themselves separate complications of specific myocytes.

Exact results for survival probability in the multistate Landau-Zener model

International Nuclear Information System (INIS)

Volkov, M V; Ostrovsky, V N

2004-01-01

An exact formula is derived for survival probability in the multistate Landau-Zener model in the special case where the initially populated state corresponds to the extremal (maximum or minimum) slope of a linear diabatic potential curve. The formula was originally guessed by S Brundobler and V Elzer (1993 J. Phys. A: Math. Gen. 26 1211) based on numerical calculations. It is a simple generalization of the expression for the probability of diabatic passage in the famous two-state Landau-Zener model. Our result is obtained via analysis and summation of the entire perturbation theory series

The effect of coupling hydrologic and hydrodynamic models on probable maximum flood estimation

Science.gov (United States)

Felder, Guido; Zischg, Andreas; Weingartner, Rolf

2017-07-01

Deterministic rainfall-runoff modelling usually assumes stationary hydrological system, as model parameters are calibrated with and therefore dependant on observed data. However, runoff processes are probably not stationary in the case of a probable maximum flood (PMF) where discharge greatly exceeds observed flood peaks. Developing hydrodynamic models and using them to build coupled hydrologic-hydrodynamic models can potentially improve the plausibility of PMF estimations. This study aims to assess the potential benefits and constraints of coupled modelling compared to standard deterministic hydrologic modelling when it comes to PMF estimation. The two modelling approaches are applied using a set of 100 spatio-temporal probable maximum precipitation (PMP) distribution scenarios. The resulting hydrographs, the resulting peak discharges as well as the reliability and the plausibility of the estimates are evaluated. The discussion of the results shows that coupling hydrologic and hydrodynamic models substantially improves the physical plausibility of PMF modelling, although both modelling approaches lead to PMF estimations for the catchment outlet that fall within a similar range. Using a coupled model is particularly suggested in cases where considerable flood-prone areas are situated within a catchment.

A Probability-Based Hybrid User Model for Recommendation System

Directory of Open Access Journals (Sweden)

Jia Hao

2016-01-01

Full Text Available With the rapid development of information communication technology, the available information or knowledge is exponentially increased, and this causes the well-known information overload phenomenon. This problem is more serious in product design corporations because over half of the valuable design time is consumed in knowledge acquisition, which highly extends the design cycle and weakens the competitiveness. Therefore, the recommender systems become very important in the domain of product domain. This research presents a probability-based hybrid user model, which is a combination of collaborative filtering and content-based filtering. This hybrid model utilizes user ratings and item topics or classes, which are available in the domain of product design, to predict the knowledge requirement. The comprehensive analysis of the experimental results shows that the proposed method gains better performance in most of the parameter settings. This work contributes a probability-based method to the community for implement recommender system when only user ratings and item topics are available.

Wind-wave modelling aspects within complicate topography

Directory of Open Access Journals (Sweden)

S. Christopoulos

Full Text Available Wave forecasting aspects for basins with complicate geomorphology, such as the Aegean Sea, are investigated through an intercomparison study. The efficiency of the available wind models (ECMWF, UKMO to reproduce wind patterns over special basins, as well as three wave models incorporating different physics and characteristics (WAM, AUT, WACCAS, are tested for selected storm cases representing the typical wind situations over the basin. From the wave results, discussed in terms of time-series and statistical parameters, the crucial role is pointed out of the wind resolution and the reliability of the different wave models to estimate the wave climate in such a basin. The necessary grid resolution is also tested, while for a specific test case (December 1991 ERS-1 satellite data are compared with those of the model.

A method of analyzing rectal surface area irradiated and rectal complications in prostate conformal radiotherapy

International Nuclear Information System (INIS)

Lu Yong; Song, Paul Y.; Li Shidong; Spelbring, Danny R.; Vijayakumar, Srinivasan; Haraf, Daniel J.; Chen, George T.Y.

1995-01-01

Purpose: To develop a method of analyzing rectal surface area irradiated and rectal complications in prostate conformal radiotherapy. Methods and Materials: Dose-surface histograms of the rectum, which state the rectal surface area irradiated to any given dose, were calculated for a group of 27 patients treated with a four-field box technique to a total (tumor minimum) dose ranging from 68 to 70 Gy. Occurrences of rectal toxicities as defined by the Radiation Therapy Oncology Group (RTOG) were recorded and examined in terms of dose and rectal surface area irradiated. For a specified end point of rectal complication, the complication probability was analyzed as a function of dose irradiated to a fixed rectal area, and as a function of area receiving a fixed dose. Lyman's model of normal tissue complication probability (NTCP) was used to fit the data. Results: The observed occurrences of rectal complications appear to depend on the rectal surface area irradiated to a given dose level. The patient distribution of each toxicity grade exhibits a maximum as a function of percentage surface area irradiated, and the maximum moves to higher values of percentage surface area as the toxicity grade increases. The dependence of the NTCP for the specified end point on dose and percentage surface area irradiated was fitted to Lyman's NTCP model with a set of parameters. The curvature of the NTCP as a function of the surface area suggests that the rectum is a parallel structured organ. Conclusions: The described method of analyzing rectal surface area irradiated yields interesting insight into understanding rectal complications in prostate conformal radiotherapy. Application of the method to a larger patient data set has the potential to facilitate the construction of a full dose-surface-complication relationship, which would be most useful in guiding clinical practice

A stochastic model for the probability of malaria extinction by mass drug administration.

Science.gov (United States)

Pemberton-Ross, Peter; Chitnis, Nakul; Pothin, Emilie; Smith, Thomas A

2017-09-18

Mass drug administration (MDA) has been proposed as an intervention to achieve local extinction of malaria. Although its effect on the reproduction number is short lived, extinction may subsequently occur in a small population due to stochastic fluctuations. This paper examines how the probability of stochastic extinction depends on population size, MDA coverage and the reproduction number under control, R c . A simple compartmental model is developed which is used to compute the probability of extinction using probability generating functions. The expected time to extinction in small populations after MDA for various scenarios in this model is calculated analytically. The results indicate that mass drug administration (Firstly, R c must be sustained at R c  95% to have a non-negligible probability of successful elimination. Stochastic fluctuations only significantly affect the probability of extinction in populations of about 1000 individuals or less. The expected time to extinction via stochastic fluctuation is less than 10 years only in populations less than about 150 individuals. Clustering of secondary infections and of MDA distribution both contribute positively to the potential probability of success, indicating that MDA would most effectively be administered at the household level. There are very limited circumstances in which MDA will lead to local malaria elimination with a substantial probability.

A Taxonomy of Latent Structure Assumptions for Probability Matrix Decomposition Models.

Science.gov (United States)

Meulders, Michel; De Boeck, Paul; Van Mechelen, Iven

2003-01-01

Proposed a taxonomy of latent structure assumptions for probability matrix decomposition (PMD) that includes the original PMD model and a three-way extension of the multiple classification latent class model. Simulation study results show the usefulness of the taxonomy. (SLD)

Modelling the Probability Density Function of IPTV Traffic Packet Delay Variation

Directory of Open Access Journals (Sweden)

Michal Halas

2012-01-01

Full Text Available This article deals with modelling the Probability density function of IPTV traffic packet delay variation. The use of this modelling is in an efficient de-jitter buffer estimation. When an IP packet travels across a network, it experiences delay and its variation. This variation is caused by routing, queueing systems and other influences like the processing delay of the network nodes. When we try to separate these at least three types of delay variation, we need a way to measure these types separately. This work is aimed to the delay variation caused by queueing systems which has the main implications to the form of the Probability density function.

Trending in Probability of Collision Measurements via a Bayesian Zero-Inflated Beta Mixed Model

Science.gov (United States)

Vallejo, Jonathon; Hejduk, Matt; Stamey, James

2015-01-01

We investigate the performance of a generalized linear mixed model in predicting the Probabilities of Collision (Pc) for conjunction events. Specifically, we apply this model to the log(sub 10) transformation of these probabilities and argue that this transformation yields values that can be considered bounded in practice. Additionally, this bounded random variable, after scaling, is zero-inflated. Consequently, we model these values using the zero-inflated Beta distribution, and utilize the Bayesian paradigm and the mixed model framework to borrow information from past and current events. This provides a natural way to model the data and provides a basis for answering questions of interest, such as what is the likelihood of observing a probability of collision equal to the effective value of zero on a subsequent observation.

Investigating the probability of detection of typical cavity shapes through modelling and comparison of geophysical techniques

Science.gov (United States)

James, P.

2011-12-01

With a growing need for housing in the U.K., the government has proposed increased development of brownfield sites. However, old mine workings and natural cavities represent a potential hazard before, during and after construction on such sites, and add further complication to subsurface parameters. Cavities are hence a limitation to certain redevelopment and their detection is an ever important consideration. The current standard technique for cavity detection is a borehole grid, which is intrusive, non-continuous, slow and expensive. A new robust investigation standard in the detection of cavities is sought and geophysical techniques offer an attractive alternative. Geophysical techniques have previously been utilised successfully in the detection of cavities in various geologies, but still has an uncertain reputation in the engineering industry. Engineers are unsure of the techniques and are inclined to rely on well known techniques than utilise new technologies. Bad experiences with geophysics are commonly due to the indiscriminate choice of particular techniques. It is imperative that a geophysical survey is designed with the specific site and target in mind at all times, and the ability and judgement to rule out some, or all, techniques. To this author's knowledge no comparative software exists to aid technique choice. Also, previous modelling software limit the shapes of bodies and hence typical cavity shapes are not represented. Here, we introduce 3D modelling software (Matlab) which computes and compares the response to various cavity targets from a range of techniques (gravity, gravity gradient, magnetic, magnetic gradient and GPR). Typical near surface cavity shapes are modelled including shafts, bellpits, various lining and capping materials, and migrating voids. The probability of cavity detection is assessed in typical subsurface and noise conditions across a range of survey parameters. Techniques can be compared and the limits of detection distance

Constructing inverse probability weights for continuous exposures: a comparison of methods.

Science.gov (United States)

Naimi, Ashley I; Moodie, Erica E M; Auger, Nathalie; Kaufman, Jay S

2014-03-01

Inverse probability-weighted marginal structural models with binary exposures are common in epidemiology. Constructing inverse probability weights for a continuous exposure can be complicated by the presence of outliers, and the need to identify a parametric form for the exposure and account for nonconstant exposure variance. We explored the performance of various methods to construct inverse probability weights for continuous exposures using Monte Carlo simulation. We generated two continuous exposures and binary outcomes using data sampled from a large empirical cohort. The first exposure followed a normal distribution with homoscedastic variance. The second exposure followed a contaminated Poisson distribution, with heteroscedastic variance equal to the conditional mean. We assessed six methods to construct inverse probability weights using: a normal distribution, a normal distribution with heteroscedastic variance, a truncated normal distribution with heteroscedastic variance, a gamma distribution, a t distribution (1, 3, and 5 degrees of freedom), and a quantile binning approach (based on 10, 15, and 20 exposure categories). We estimated the marginal odds ratio for a single-unit increase in each simulated exposure in a regression model weighted by the inverse probability weights constructed using each approach, and then computed the bias and mean squared error for each method. For the homoscedastic exposure, the standard normal, gamma, and quantile binning approaches performed best. For the heteroscedastic exposure, the quantile binning, gamma, and heteroscedastic normal approaches performed best. Our results suggest that the quantile binning approach is a simple and versatile way to construct inverse probability weights for continuous exposures.

Risk Prediction Model for Severe Postoperative Complication in Bariatric Surgery.

Science.gov (United States)

Stenberg, Erik; Cao, Yang; Szabo, Eva; Näslund, Erik; Näslund, Ingmar; Ottosson, Johan

2018-01-12

Factors associated with risk for adverse outcome are important considerations in the preoperative assessment of patients for bariatric surgery. As yet, prediction models based on preoperative risk factors have not been able to predict adverse outcome sufficiently. This study aimed to identify preoperative risk factors and to construct a risk prediction model based on these. Patients who underwent a bariatric surgical procedure in Sweden between 2010 and 2014 were identified from the Scandinavian Obesity Surgery Registry (SOReg). Associations between preoperative potential risk factors and severe postoperative complications were analysed using a logistic regression model. A multivariate model for risk prediction was created and validated in the SOReg for patients who underwent bariatric surgery in Sweden, 2015. Revision surgery (standardized OR 1.19, 95% confidence interval (CI) 1.14-0.24, p prediction model. Despite high specificity, the sensitivity of the model was low. Revision surgery, high age, low BMI, large waist circumference, and dyspepsia/GERD were associated with an increased risk for severe postoperative complication. The prediction model based on these factors, however, had a sensitivity that was too low to predict risk in the individual patient case.

Normal Tissue Complication Probability Analysis of Acute Gastrointestinal Toxicity in Cervical Cancer Patients Undergoing Intensity Modulated Radiation Therapy and Concurrent Cisplatin

International Nuclear Information System (INIS)

Simpson, Daniel R.; Song, William Y.; Moiseenko, Vitali; Rose, Brent S.; Yashar, Catheryn M.; Mundt, Arno J.; Mell, Loren K.

2012-01-01

Purpose: To test the hypothesis that increased bowel radiation dose is associated with acute gastrointestinal (GI) toxicity in cervical cancer patients undergoing concurrent chemotherapy and intensity-modulated radiation therapy (IMRT), using a previously derived normal tissue complication probability (NTCP) model. Methods: Fifty patients with Stage I–III cervical cancer undergoing IMRT and concurrent weekly cisplatin were analyzed. Acute GI toxicity was graded using the Radiation Therapy Oncology Group scale, excluding upper GI events. A logistic model was used to test correlations between acute GI toxicity and bowel dosimetric parameters. The primary objective was to test the association between Grade ≥2 GI toxicity and the volume of bowel receiving ≥45 Gy (V 45 ) using the logistic model. Results: Twenty-three patients (46%) had Grade ≥2 GI toxicity. The mean (SD) V 45 was 143 mL (99). The mean V 45 values for patients with and without Grade ≥2 GI toxicity were 176 vs. 115 mL, respectively. Twenty patients (40%) had V 45 >150 mL. The proportion of patients with Grade ≥2 GI toxicity with and without V 45 >150 mL was 65% vs. 33% (p = 0.03). Logistic model parameter estimates V50 and γ were 161 mL (95% confidence interval [CI] 60–399) and 0.31 (95% CI 0.04–0.63), respectively. On multivariable logistic regression, increased V 45 was associated with an increased odds of Grade ≥2 GI toxicity (odds ratio 2.19 per 100 mL, 95% CI 1.04–4.63, p = 0.04). Conclusions: Our results support the hypothesis that increasing bowel V 45 is correlated with increased GI toxicity in cervical cancer patients undergoing IMRT and concurrent cisplatin. Reducing bowel V 45 could reduce the risk of Grade ≥2 GI toxicity by approximately 50% per 100 mL of bowel spared.

Modelling the Probability of Landslides Impacting Road Networks

Science.gov (United States)

Taylor, F. E.; Malamud, B. D.

2012-04-01

During a landslide triggering event, the threat of landslides blocking roads poses a risk to logistics, rescue efforts and communities dependant on those road networks. Here we present preliminary results of a stochastic model we have developed to evaluate the probability of landslides intersecting a simple road network during a landslide triggering event and apply simple network indices to measure the state of the road network in the affected region. A 4000 x 4000 cell array with a 5 m x 5 m resolution was used, with a pre-defined simple road network laid onto it, and landslides 'randomly' dropped onto it. Landslide areas (AL) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power-law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL; the rollover (maximum probability) occurs at about AL = 400 m2 This statistical distribution was chosen based on three substantially complete triggered landslide inventories recorded in existing literature. The number of landslide areas (NL) selected for each triggered event iteration was chosen to have an average density of 1 landslide km-2, i.e. NL = 400 landslide areas chosen randomly for each iteration, and was based on several existing triggered landslide event inventories. A simple road network was chosen, in a 'T' shape configuration, with one road 1 x 4000 cells (5 m x 20 km) in a 'T' formation with another road 1 x 2000 cells (5 m x 10 km). The landslide areas were then randomly 'dropped' over the road array and indices such as the location, size (ABL) and number of road blockages (NBL) recorded. This process was performed 500 times (iterations) in a Monte-Carlo type simulation. Initial results show that for a landslide triggering event with 400 landslides over a 400 km2 region, the number of road blocks per iteration, NBL,ranges from 0 to 7. The average blockage area for the 500 iterations (A¯ BL) is about 3000 m

The probabilities of one- and multi-track events for modeling radiation-induced cell kill

Energy Technology Data Exchange (ETDEWEB)

Schneider, Uwe; Vasi, Fabiano; Besserer, Juergen [University of Zuerich, Department of Physics, Science Faculty, Zurich (Switzerland); Radiotherapy Hirslanden, Zurich (Switzerland)

2017-08-15

In view of the clinical importance of hypofractionated radiotherapy, track models which are based on multi-hit events are currently reinvestigated. These models are often criticized, because it is believed that the probability of multi-track hits is negligible. In this work, the probabilities for one- and multi-track events are determined for different biological targets. The obtained probabilities can be used with nano-dosimetric cluster size distributions to obtain the parameters of track models. We quantitatively determined the probabilities for one- and multi-track events for 100, 500 and 1000 keV electrons, respectively. It is assumed that the single tracks are statistically independent and follow a Poisson distribution. Three different biological targets were investigated: (1) a DNA strand (2 nm scale); (2) two adjacent chromatin fibers (60 nm); and (3) fiber loops (300 nm). It was shown that the probabilities for one- and multi-track events are increasing with energy, size of the sensitive target structure, and dose. For a 2 x 2 x 2 nm{sup 3} target, one-track events are around 10,000 times more frequent than multi-track events. If the size of the sensitive structure is increased to 100-300 nm, the probabilities for one- and multi-track events are of the same order of magnitude. It was shown that target theories can play a role for describing radiation-induced cell death if the targets are of the size of two adjacent chromatin fibers or fiber loops. The obtained probabilities can be used together with the nano-dosimetric cluster size distributions to determine model parameters for target theories. (orig.)

Discounting of Monetary Rewards that are Both Delayed and Probabilistic: Delay and Probability Combine Multiplicatively, not Additively

Science.gov (United States)

Vanderveldt, Ariana; Green, Leonard; Myerson, Joel

2014-01-01

The value of an outcome is affected both by the delay until its receipt (delay discounting) and by the likelihood of its receipt (probability discounting). Despite being well-described by the same hyperboloid function, delay and probability discounting involve fundamentally different processes, as revealed, for example, by the differential effects of reward amount. Previous research has focused on the discounting of delayed and probabilistic rewards separately, with little research examining more complex situations in which rewards are both delayed and probabilistic. In two experiments, participants made choices between smaller rewards that were both immediate and certain and larger rewards that were both delayed and probabilistic. Analyses revealed significant interactions between delay and probability factors inconsistent with an additive model. In contrast, a hyperboloid discounting model in which delay and probability were combined multiplicatively provided an excellent fit to the data. These results suggest that the hyperboloid is a good descriptor of decision making in complicated monetary choice situations like those people encounter in everyday life. PMID:24933696

Leveraging electronic health records for predictive modeling of post-surgical complications.

Science.gov (United States)

Weller, Grant B; Lovely, Jenna; Larson, David W; Earnshaw, Berton A; Huebner, Marianne

2017-01-01

Hospital-specific electronic health record systems are used to inform clinical practice about best practices and quality improvements. Many surgical centers have developed deterministic clinical decision rules to discover adverse events (e.g. postoperative complications) using electronic health record data. However, these data provide opportunities to use probabilistic methods for early prediction of adverse health events, which may be more informative than deterministic algorithms. Electronic health record data from a set of 9598 colorectal surgery cases from 2010 to 2014 were used to predict the occurrence of selected complications including surgical site infection, ileus, and bleeding. Consistent with previous studies, we find a high rate of missing values for both covariates and complication information (4-90%). Several machine learning classification methods are trained on an 80% random sample of cases and tested on a remaining holdout set. Predictive performance varies by complication, although an area under the receiver operating characteristic curve as high as 0.86 on testing data was achieved for bleeding complications, and accuracy for all complications compares favorably to existing clinical decision rules. Our results confirm that electronic health records provide opportunities for improved risk prediction of surgical complications; however, consideration of data quality and consistency standards is an important step in predictive modeling with such data.

Capacity analysis in multi-state synaptic models: a retrieval probability perspective.

Science.gov (United States)

Huang, Yibi; Amit, Yali

2011-06-01

We define the memory capacity of networks of binary neurons with finite-state synapses in terms of retrieval probabilities of learned patterns under standard asynchronous dynamics with a predetermined threshold. The threshold is set to control the proportion of non-selective neurons that fire. An optimal inhibition level is chosen to stabilize network behavior. For any local learning rule we provide a computationally efficient and highly accurate approximation to the retrieval probability of a pattern as a function of its age. The method is applied to the sequential models (Fusi and Abbott, Nat Neurosci 10:485-493, 2007) and meta-plasticity models (Fusi et al., Neuron 45(4):599-611, 2005; Leibold and Kempter, Cereb Cortex 18:67-77, 2008). We show that as the number of synaptic states increases, the capacity, as defined here, either plateaus or decreases. In the few cases where multi-state models exceed the capacity of binary synapse models the improvement is small.

Early bowel complications following radiotherapy of uterine cervix carcinoma

International Nuclear Information System (INIS)

Kim, Won Dong

1999-01-01

This study evaluated early bowel complications in cervix cancer patients, following external radiotherapy (ERT) and high dose rate intracavitary radiation (HDR ICR). Factors affecting the risk of developing early bowel complications and its incidence are analyzed and discussed. The study is the retrospective review of 66 patients who received radiotherapy at Chungbuk National University Hospital from April 1994 to December 1998. The patients underwent 41.4 or 50.4 Gy ERT according to FIGO stage and tumor size, then A point dose was boosted to 71.4 or 74.4 Gy using a remotely controlled after loading Buchler HDR ICR. The EORTC/RTOG morbidity criteria were used to grade early bowel complications, which are valid from day 1, the commencement of therapy, through day 90. The actuarial incidence, severity of complications were investigated and clinical pretreatment factors relevant to complications were found through univariate (Wilcoxon) and multivariate (Cox proportional hazard model) analysis. Of the 66 patients, 30 patients (46%) developed early bowel complications; 25 patients (38%) with grade 1 or 2, 4 patients (6%) with grade 3 and 1 patient (2%) with grade 4. The complications usually began to occur 3 weeks after the commencement of radiotherapy. The actuarial incidence of early bowel complications was 41% at 10 weeks. The early bowel complications were associated significantly with an old age and a history of previous abdomino-pelvic surgery. All three patients who had a protracted overall treatment time (about 2 weeks) due to severe bowel complication, suffered from pelvic recurrences. Forty six percent of patients experienced early bowel complications, most of which were grade 1 or 2 and relieved spontaneously or by medication. The patients with an old age or a previous surgery have a high probability of early complications and they may be less compliant with planned radiotherapy. So more careful precaution is necessary for these patients

Elements of probability and statistics an introduction to probability with De Finetti’s approach and to Bayesian statistics

CERN Document Server

Biagini, Francesca

2016-01-01

This book provides an introduction to elementary probability and to Bayesian statistics using de Finetti's subjectivist approach. One of the features of this approach is that it does not require the introduction of sample space – a non-intrinsic concept that makes the treatment of elementary probability unnecessarily complicate – but introduces as fundamental the concept of random numbers directly related to their interpretation in applications. Events become a particular case of random numbers and probability a particular case of expectation when it is applied to events. The subjective evaluation of expectation and of conditional expectation is based on an economic choice of an acceptable bet or penalty. The properties of expectation and conditional expectation are derived by applying a coherence criterion that the evaluation has to follow. The book is suitable for all introductory courses in probability and statistics for students in Mathematics, Informatics, Engineering, and Physics.

Traffic simulation based ship collision probability modeling

Energy Technology Data Exchange (ETDEWEB)

Goerlandt, Floris, E-mail: floris.goerlandt@tkk.f [Aalto University, School of Science and Technology, Department of Applied Mechanics, Marine Technology, P.O. Box 15300, FI-00076 AALTO, Espoo (Finland); Kujala, Pentti [Aalto University, School of Science and Technology, Department of Applied Mechanics, Marine Technology, P.O. Box 15300, FI-00076 AALTO, Espoo (Finland)

2011-01-15

Maritime traffic poses various risks in terms of human, environmental and economic loss. In a risk analysis of ship collisions, it is important to get a reasonable estimate for the probability of such accidents and the consequences they lead to. In this paper, a method is proposed to assess the probability of vessels colliding with each other. The method is capable of determining the expected number of accidents, the locations where and the time when they are most likely to occur, while providing input for models concerned with the expected consequences. At the basis of the collision detection algorithm lays an extensive time domain micro-simulation of vessel traffic in the given area. The Monte Carlo simulation technique is applied to obtain a meaningful prediction of the relevant factors of the collision events. Data obtained through the Automatic Identification System is analyzed in detail to obtain realistic input data for the traffic simulation: traffic routes, the number of vessels on each route, the ship departure times, main dimensions and sailing speed. The results obtained by the proposed method for the studied case of the Gulf of Finland are presented, showing reasonable agreement with registered accident and near-miss data.

Success probability orientated optimization model for resource allocation of the technological innovation multi-project system

Institute of Scientific and Technical Information of China (English)

Weixu Dai; Weiwei Wu; Bo Yu; Yunhao Zhu

2016-01-01

A success probability orientated optimization model for resource al ocation of the technological innovation multi-project system is studied. Based on the definition of the technological in-novation multi-project system, the leveling optimization of cost and success probability is set as the objective of resource al ocation. The cost function and the probability function of the optimization model are constructed. Then the objective function of the model is constructed and the solving process is explained. The model is applied to the resource al ocation of an enterprise’s technological innovation multi-project system. The results show that the pro-posed model is more effective in rational resource al ocation, and is more applicable in maximizing the utility of the technological innovation multi-project system.

Probability, Nondeterminism and Concurrency

DEFF Research Database (Denmark)

Varacca, Daniele

Nondeterminism is modelled in domain theory by the notion of a powerdomain, while probability is modelled by that of the probabilistic powerdomain. Some problems arise when we want to combine them in order to model computation in which both nondeterminism and probability are present. In particula...

SILENE and TDT: A code for collision probability calculations in XY geometries

International Nuclear Information System (INIS)

Sanchez, R.; Stankovski, Z.

1993-01-01

Collision probability methods are routinely used for cell and assembly multigroup transport calculations in core design tasks. Collision probability methods use a specialized tracking routine to compute neutron trajectories within a given geometric object. These trajectories are then used to generate the appropriate collision matrices in as many groups as required. Traditional tracking routines are based on open-quotes globalclose quotes geometric descriptions (such as regular meshes) and are not able to cope with the geometric detail required in actual core calculations. Therefore, users have to modify their geometry in order to match the geometric model accepted by the tracking routine, introducing thus a modeling error whose evaluation requires the use of a open-quotes referenceclose quotes method. Recently, an effort has been made to develop more flexible tracking routines either by directly adopting tracking Monte Carlo techniques or by coding of complicated geometries. Among these, the SILENE and TDT package is being developed at the Commissariat a l' Energie Atomique to provide routine as well as reference calculations in arbitrarily shaped XY geometries. This package combines a direct graphical acquisition system (SILENE) together with a node-based collision probability code for XY geometries (TDT)

Estimating Model Probabilities using Thermodynamic Markov Chain Monte Carlo Methods

Science.gov (United States)

Ye, M.; Liu, P.; Beerli, P.; Lu, D.; Hill, M. C.

2014-12-01

Markov chain Monte Carlo (MCMC) methods are widely used to evaluate model probability for quantifying model uncertainty. In a general procedure, MCMC simulations are first conducted for each individual model, and MCMC parameter samples are then used to approximate marginal likelihood of the model by calculating the geometric mean of the joint likelihood of the model and its parameters. It has been found the method of evaluating geometric mean suffers from the numerical problem of low convergence rate. A simple test case shows that even millions of MCMC samples are insufficient to yield accurate estimation of the marginal likelihood. To resolve this problem, a thermodynamic method is used to have multiple MCMC runs with different values of a heating coefficient between zero and one. When the heating coefficient is zero, the MCMC run is equivalent to a random walk MC in the prior parameter space; when the heating coefficient is one, the MCMC run is the conventional one. For a simple case with analytical form of the marginal likelihood, the thermodynamic method yields more accurate estimate than the method of using geometric mean. This is also demonstrated for a case of groundwater modeling with consideration of four alternative models postulated based on different conceptualization of a confining layer. This groundwater example shows that model probabilities estimated using the thermodynamic method are more reasonable than those obtained using the geometric method. The thermodynamic method is general, and can be used for a wide range of environmental problem for model uncertainty quantification.

Modeling Perceived Quality, Customer Satisfaction and Probability of Guest Returning to the Destination

Directory of Open Access Journals (Sweden)

Olivera Blagojevic Popovic

2018-03-01

Full Text Available In the hotel industry, it is a well-known fact that, despite of quality and variety of services provided, there is a low probability that the guests will return. This research is focused on identifying the basic factors of the hotel offer, which could determine the influence on the correlation between the guests’ satisfaction and the probability of their return. The objective of the article is to explore the relationship between the guests’ satisfaction with the quality hotel services in total (including the tourist offer of the place and the probability of his return to the same destination. The questionnaire method was applied in the survey, and the data were analysed based on factor analysis. Thereafter, the model for forecasting the probability of the guests returning to the destination was established, by using the example of Montenegrin tourism. The model represents a defined framework for the guest’s decision-making process. It identifies two main characteristics of guest experiences: satisfaction and rated quality (of the destination’s overall hotel service and tourist offer. The same model evaluates the impact of the above factors on the probability of the guests’ returning to the same destination. The starting hypothesis was the existence of a high degree of correlation between the guests’ satisfaction (with the destination’s hotel services and tourist offer and the probability of returning to the selected Montenegrin destinations. The research confirmed the above-mentioned hypothesis. The results have revealed that there are significant differences in perceived quality, i.e. satisfaction between the target groups of Eastern and Western European tourists

Identification of Patient Benefit From Proton Therapy for Advanced Head and Neck Cancer Patients Based on Individual and Subgroup Normal Tissue Complication Probability Analysis

International Nuclear Information System (INIS)

Jakobi, Annika; Bandurska-Luque, Anna; Stützer, Kristin; Haase, Robert; Löck, Steffen; Wack, Linda-Jacqueline; Mönnich, David; Thorwarth, Daniela

2015-01-01

Purpose: The purpose of this study was to determine, by treatment plan comparison along with normal tissue complication probability (NTCP) modeling, whether a subpopulation of patients with head and neck squamous cell carcinoma (HNSCC) could be identified that would gain substantial benefit from proton therapy in terms of NTCP. Methods and Materials: For 45 HNSCC patients, intensity modulated radiation therapy (IMRT) was compared to intensity modulated proton therapy (IMPT). Physical dose distributions were evaluated as well as the resulting NTCP values, using modern models for acute mucositis, xerostomia, aspiration, dysphagia, laryngeal edema, and trismus. Patient subgroups were defined based on primary tumor location. Results: Generally, IMPT reduced the NTCP values while keeping similar target coverage for all patients. Subgroup analyses revealed a higher individual reduction of swallowing-related side effects by IMPT for patients with tumors in the upper head and neck area, whereas the risk reduction of acute mucositis was more pronounced in patients with tumors in the larynx region. More patients with tumors in the upper head and neck area had a reduction in NTCP of more than 10%. Conclusions: Subgrouping can help to identify patients who may benefit more than others from the use of IMPT and, thus, can be a useful tool for a preselection of patients in the clinic where there are limited PT resources. Because the individual benefit differs within a subgroup, the relative merits should additionally be evaluated by individual treatment plan comparisons

Identification of Patient Benefit From Proton Therapy for Advanced Head and Neck Cancer Patients Based on Individual and Subgroup Normal Tissue Complication Probability Analysis

Energy Technology Data Exchange (ETDEWEB)

Jakobi, Annika, E-mail: Annika.Jakobi@OncoRay.de [OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Bandurska-Luque, Anna [OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Department of Radiation Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden (Germany); Stützer, Kristin; Haase, Robert; Löck, Steffen [OncoRay-National Center for Radiation Research in Oncology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Helmholtz-Zentrum Dresden-Rossendorf, Dresden (Germany); Wack, Linda-Jacqueline [Section for Biomedical Physics, University Hospital for Radiation Oncology, Eberhard Karls Universät Tübingen (Germany); Mönnich, David [Section for Biomedical Physics, University Hospital for Radiation Oncology, Eberhard Karls Universät Tübingen (Germany); German Cancer Research Center, Heidelberg (Germany); German Cancer Consortium, Tübingen (Germany); Thorwarth, Daniela [Section for Biomedical Physics, University Hospital for Radiation Oncology, Eberhard Karls Universät Tübingen (Germany); and others

2015-08-01

Purpose: The purpose of this study was to determine, by treatment plan comparison along with normal tissue complication probability (NTCP) modeling, whether a subpopulation of patients with head and neck squamous cell carcinoma (HNSCC) could be identified that would gain substantial benefit from proton therapy in terms of NTCP. Methods and Materials: For 45 HNSCC patients, intensity modulated radiation therapy (IMRT) was compared to intensity modulated proton therapy (IMPT). Physical dose distributions were evaluated as well as the resulting NTCP values, using modern models for acute mucositis, xerostomia, aspiration, dysphagia, laryngeal edema, and trismus. Patient subgroups were defined based on primary tumor location. Results: Generally, IMPT reduced the NTCP values while keeping similar target coverage for all patients. Subgroup analyses revealed a higher individual reduction of swallowing-related side effects by IMPT for patients with tumors in the upper head and neck area, whereas the risk reduction of acute mucositis was more pronounced in patients with tumors in the larynx region. More patients with tumors in the upper head and neck area had a reduction in NTCP of more than 10%. Conclusions: Subgrouping can help to identify patients who may benefit more than others from the use of IMPT and, thus, can be a useful tool for a preselection of patients in the clinic where there are limited PT resources. Because the individual benefit differs within a subgroup, the relative merits should additionally be evaluated by individual treatment plan comparisons.

Diagnostics of enterprise bankruptcy occurrence probability in an anti-crisis management: modern approaches and classification of models

Directory of Open Access Journals (Sweden)

I.V. Zhalinska

2015-09-01

Full Text Available Diagnostics of enterprise bankruptcy occurrence probability is defined as an important tool ensuring the viability of an organization under conditions of unpredictable dynamic environment. The paper aims to define the basic features of diagnostics of bankruptcy occurrence probability models and their classification. The article grounds the objective increasing of crisis probability in modern enterprises where such increasing leads to the need to improve the efficiency of anti-crisis enterprise activities. The system of anti-crisis management is based on the subsystem of diagnostics of bankruptcy occurrence probability. Such a subsystem is the main one for further measures to prevent and overcome the crisis. The classification of existing models of enterprise bankruptcy occurrence probability has been suggested. The classification is based on methodical and methodological principles of models. The following main groups of models are determined: the models using financial ratios, aggregates and scores, the models of discriminated analysis, the methods of strategic analysis, informal models, artificial intelligence systems and the combination of the models. The classification made it possible to identify the analytical capabilities of each of the groups of models suggested.

An extended car-following model considering random safety distance with different probabilities

Science.gov (United States)

Wang, Jufeng; Sun, Fengxin; Cheng, Rongjun; Ge, Hongxia; Wei, Qi

2018-02-01

Because of the difference in vehicle type or driving skill, the driving strategy is not exactly the same. The driving speeds of the different vehicles may be different for the same headway. Since the optimal velocity function is just determined by the safety distance besides the maximum velocity and headway, an extended car-following model accounting for random safety distance with different probabilities is proposed in this paper. The linear stable condition for this extended traffic model is obtained by using linear stability theory. Numerical simulations are carried out to explore the complex phenomenon resulting from multiple safety distance in the optimal velocity function. The cases of multiple types of safety distances selected with different probabilities are presented. Numerical results show that the traffic flow with multiple safety distances with different probabilities will be more unstable than that with single type of safety distance, and will result in more stop-and-go phenomena.

Protein single-model quality assessment by feature-based probability density functions.

Science.gov (United States)

Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

Radiation related complications after ruthenium plaque radiotherapy of uveal melanoma

Energy Technology Data Exchange (ETDEWEB)

Summanen, P.; Immonen, I.; Kivela, T.; Tommila, P.; Tarkkanen, A. [Helsinki Univ. Central Hospital (Finland). Meilahti Clinic; Heikkonen, J. [Helsinki Univ. (Finland). Dept of Radiotherapy and Oncology

1996-08-01

The aims were to analyse radiation related complications and secondary enucleation after irradiation of malignant uveal melanoma with ruthenium-106 plaques. A series of 100 consecutive eyes irradiated in 1981-91 was analysed using the life table method and the Cox proportional hazards model. The 3 and 5 year probabilities of being without radiation cataract were 73% and 63%, without neovascular glaucoma 91% and 81%, without vitreous haemorrhage 83% and 74%, without radiation maculopathy 85% and 70%, and without radiation optic neuropathy 90% and 88%, respectively. (Author).

Radiation related complications after ruthenium plaque radiotherapy of uveal melanoma

International Nuclear Information System (INIS)

Summanen, P.; Immonen, I.; Kivela, T.; Tommila, P.; Tarkkanen, A.; Heikkonen, J.

1996-01-01

The aims were to analyse radiation related complications and secondary enucleation after irradiation of malignant uveal melanoma with ruthenium-106 plaques. A series of 100 consecutive eyes irradiated in 1981-91 was analysed using the life table method and the Cox proportional hazards model. The 3 and 5 year probabilities of being without radiation cataract were 73% and 63%, without neovascular glaucoma 91% and 81%, without vitreous haemorrhage 83% and 74%, without radiation maculopathy 85% and 70%, and without radiation optic neuropathy 90% and 88%, respectively. (Author)

On New Cautious Structural Reliability Models in the Framework of imprecise Probabilities

DEFF Research Database (Denmark)

Utkin, Lev V.; Kozine, Igor

2010-01-01

models and gen-eralizing conventional ones to imprecise probabili-ties. The theoretical setup employed for this purpose is imprecise statistical reasoning (Walley 1991), whose general framework is provided by upper and lower previsions (expectations). The appeal of this theory is its ability to capture......Uncertainty of parameters in engineering design has been modeled in different frameworks such as inter-val analysis, fuzzy set and possibility theories, ran-dom set theory and imprecise probability theory. The authors of this paper for many years have been de-veloping new imprecise reliability...... both aleatory (stochas-tic) and epistemic uncertainty and the flexibility with which information can be represented. The previous research of the authors related to generalizing structural reliability models to impre-cise statistical measures is summarized in Utkin & Kozine (2002) and Utkin (2004...

[Gastroplasty: complications and their prevention].

Science.gov (United States)

Schlienger, J L; Meyer, L; Rohr, S; Pradignac, A; Perrin, A E; Meyer, C; Simon, C

2003-02-01

Bariatric surgery is now frequently proposed for the treatment of morbid or complicated obesity since the introduction of minimally invasive laparoscopic anti-obesity operations such as the adjustable silicone gastric binding gastroplasty. However this reversible procedure in not always as safe as presumed and the results in weight loss may be sometimes disappointing. Side effects are common and early or late complications occured in more than 20% out of the patients. They are favoured by post operative eating disorders. Nutritional consequences are probably underestimated and are not limited to uncomfortable digestive symptoms. Some deficiencies in micronutriments have been described. The worsening of previous eating disorders or psychosocial abnormalities are not seldom. Gastroplasty is not an harmless procedure. A good selection in patients, a regular follow up, nutritional advices and psychosocial management by a multidisciplinar team are required to reduce complications after gastroplasty.

Compact baby universe model in ten dimension and probability function of quantum gravity

International Nuclear Information System (INIS)

Yan Jun; Hu Shike

1991-01-01

The quantum probability functions are calculated for ten-dimensional compact baby universe model. The authors find that the probability for the Yang-Mills baby universe to undergo a spontaneous compactification down to a four-dimensional spacetime is greater than that to remain in the original homogeneous multidimensional state. Some questions about large-wormhole catastrophe are also discussed

Geometric modeling in probability and statistics

CERN Document Server

Calin, Ovidiu

2014-01-01

This book covers topics of Informational Geometry, a field which deals with the differential geometric study of the manifold probability density functions. This is a field that is increasingly attracting the interest of researchers from many different areas of science, including mathematics, statistics, geometry, computer science, signal processing, physics and neuroscience. It is the authors’ hope that the present book will be a valuable reference for researchers and graduate students in one of the aforementioned fields. This textbook is a unified presentation of differential geometry and probability theory, and constitutes a text for a course directed at graduate or advanced undergraduate students interested in applications of differential geometry in probability and statistics. The book contains over 100 proposed exercises meant to help students deepen their understanding, and it is accompanied by software that is able to provide numerical computations of several information geometric objects. The reader...

Modeling Plan-Related Clinical Complications Using Machine Learning Tools in a Multiplan IMRT Framework

International Nuclear Information System (INIS)

Zhang, Hao H.; D'Souza, Warren D.; Shi Leyuan; Meyer, Robert R.

2009-01-01

Purpose: To predict organ-at-risk (OAR) complications as a function of dose-volume (DV) constraint settings without explicit plan computation in a multiplan intensity-modulated radiotherapy (IMRT) framework. Methods and Materials: Several plans were generated by varying the DV constraints (input features) on the OARs (multiplan framework), and the DV levels achieved by the OARs in the plans (plan properties) were modeled as a function of the imposed DV constraint settings. OAR complications were then predicted for each of the plans by using the imposed DV constraints alone (features) or in combination with modeled DV levels (plan properties) as input to machine learning (ML) algorithms. These ML approaches were used to model two OAR complications after head-and-neck and prostate IMRT: xerostomia, and Grade 2 rectal bleeding. Two-fold cross-validation was used for model verification and mean errors are reported. Results: Errors for modeling the achieved DV values as a function of constraint settings were 0-6%. In the head-and-neck case, the mean absolute prediction error of the saliva flow rate normalized to the pretreatment saliva flow rate was 0.42% with a 95% confidence interval of (0.41-0.43%). In the prostate case, an average prediction accuracy of 97.04% with a 95% confidence interval of (96.67-97.41%) was achieved for Grade 2 rectal bleeding complications. Conclusions: ML can be used for predicting OAR complications during treatment planning allowing for alternative DV constraint settings to be assessed within the planning framework.

Digital dice computational solutions to practical probability problems

CERN Document Server

Nahin, Paul J

2013-01-01

Some probability problems are so difficult that they stump the smartest mathematicians. But even the hardest of these problems can often be solved with a computer and a Monte Carlo simulation, in which a random-number generator simulates a physical process, such as a million rolls of a pair of dice. This is what Digital Dice is all about: how to get numerical answers to difficult probability problems without having to solve complicated mathematical equations. Popular-math writer Paul Nahin challenges readers to solve twenty-one difficult but fun problems, from determining the

Height probabilities in the Abelian sandpile model on the generalized finite Bethe lattice

Science.gov (United States)

Chen, Haiyan; Zhang, Fuji

2013-08-01

In this paper, we study the sandpile model on the generalized finite Bethe lattice with a particular boundary condition. Using a combinatorial method, we give the exact expressions for all single-site probabilities and some two-site joint probabilities. As a by-product, we prove that the height probabilities of bulk vertices are all the same for the Bethe lattice with certain given boundary condition, which was found from numerical evidence by Grassberger and Manna ["Some more sandpiles," J. Phys. (France) 51, 1077-1098 (1990)], 10.1051/jphys:0199000510110107700 but without a proof.

Direct modeling of regression effects for transition probabilities in the progressive illness-death model

DEFF Research Database (Denmark)

Azarang, Leyla; Scheike, Thomas; de Uña-Álvarez, Jacobo

2017-01-01

In this work, we present direct regression analysis for the transition probabilities in the possibly non-Markov progressive illness–death model. The method is based on binomial regression, where the response is the indicator of the occupancy for the given state along time. Randomly weighted score...

An empirical probability model of detecting species at low densities.

Science.gov (United States)

Delaney, David G; Leung, Brian

2010-06-01

False negatives, not detecting things that are actually present, are an important but understudied problem. False negatives are the result of our inability to perfectly detect species, especially those at low density such as endangered species or newly arriving introduced species. They reduce our ability to interpret presence-absence survey data and make sound management decisions (e.g., rapid response). To reduce the probability of false negatives, we need to compare the efficacy and sensitivity of different sampling approaches and quantify an unbiased estimate of the probability of detection. We conducted field experiments in the intertidal zone of New England and New York to test the sensitivity of two sampling approaches (quadrat vs. total area search, TAS), given different target characteristics (mobile vs. sessile). Using logistic regression we built detection curves for each sampling approach that related the sampling intensity and the density of targets to the probability of detection. The TAS approach reduced the probability of false negatives and detected targets faster than the quadrat approach. Mobility of targets increased the time to detection but did not affect detection success. Finally, we interpreted two years of presence-absence data on the distribution of the Asian shore crab (Hemigrapsus sanguineus) in New England and New York, using our probability model for false negatives. The type of experimental approach in this paper can help to reduce false negatives and increase our ability to detect species at low densities by refining sampling approaches, which can guide conservation strategies and management decisions in various areas of ecology such as conservation biology and invasion ecology.

Fitting the Probability Distribution Functions to Model Particulate Matter Concentrations

International Nuclear Information System (INIS)

El-Shanshoury, Gh.I.

2017-01-01

The main objective of this study is to identify the best probability distribution and the plotting position formula for modeling the concentrations of Total Suspended Particles (TSP) as well as the Particulate Matter with an aerodynamic diameter<10 μm (PM 10 ). The best distribution provides the estimated probabilities that exceed the threshold limit given by the Egyptian Air Quality Limit value (EAQLV) as well the number of exceedance days is estimated. The standard limits of the EAQLV for TSP and PM 10 concentrations are 24-h average of 230 μg/m 3 and 70 μg/m 3 , respectively. Five frequency distribution functions with seven formula of plotting positions (empirical cumulative distribution functions) are compared to fit the average of daily TSP and PM 10 concentrations in year 2014 for Ain Sokhna city. The Quantile-Quantile plot (Q-Q plot) is used as a method for assessing how closely a data set fits a particular distribution. A proper probability distribution that represents the TSP and PM 10 has been chosen based on the statistical performance indicator values. The results show that Hosking and Wallis plotting position combined with Frechet distribution gave the highest fit for TSP and PM 10 concentrations. Burr distribution with the same plotting position follows Frechet distribution. The exceedance probability and days over the EAQLV are predicted using Frechet distribution. In 2014, the exceedance probability and days for TSP concentrations are 0.052 and 19 days, respectively. Furthermore, the PM 10 concentration is found to exceed the threshold limit by 174 days

Simulation of intersection of complicated information signals in air traffic control systems

Directory of Open Access Journals (Sweden)

Е. В. Коба

2000-12-01

Full Text Available Considered is the problem of complicated system simulation with customers incoming flows. Developed is an algorithm accelerated of finding probability of the superposition of complicated customers. Derived are the top and bottom estimates of damage-factor which are connected with complical customers superposition. Noticed is connection with simulation problem of air traffic control system

Fishnet model for failure probability tail of nacre-like imbricated lamellar materials

Science.gov (United States)

Luo, Wen; Bažant, Zdeněk P.

2017-12-01

Nacre, the iridescent material of the shells of pearl oysters and abalone, consists mostly of aragonite (a form of CaCO3), a brittle constituent of relatively low strength (≈10 MPa). Yet it has astonishing mean tensile strength (≈150 MPa) and fracture energy (≈350 to 1,240 J/m2). The reasons have recently become well understood: (i) the nanoscale thickness (≈300 nm) of nacre's building blocks, the aragonite lamellae (or platelets), and (ii) the imbricated, or staggered, arrangement of these lamellea, bound by biopolymer layers only ≈25 nm thick, occupying engineering applications, however, the failure probability of ≤10-6 is generally required. To guarantee it, the type of probability density function (pdf) of strength, including its tail, must be determined. This objective, not pursued previously, is hardly achievable by experiments alone, since >10^8 tests of specimens would be needed. Here we outline a statistical model of strength that resembles a fishnet pulled diagonally, captures the tail of pdf of strength and, importantly, allows analytical safety assessments of nacreous materials. The analysis shows that, in terms of safety, the imbricated lamellar structure provides a major additional advantage—˜10% strength increase at tail failure probability 10^-6 and a 1 to 2 orders of magnitude tail probability decrease at fixed stress. Another advantage is that a high scatter of microstructure properties diminishes the strength difference between the mean and the probability tail, compared with the weakest link model. These advantages of nacre-like materials are here justified analytically and supported by millions of Monte Carlo simulations.

WE-AB-204-02: Molecular-Imaging Based Assessment of Liver Complications for Yttrium-90 Microsphere Treatments: Can Existing NTCP Models Explain Clinical Outcomes?

Energy Technology Data Exchange (ETDEWEB)

Lin, M; Choi, E; Chuong, M; Saboury, B; Moeslein, F; D’Souza, W; Guerrero, M [University of Maryland School of Medicine, Baltimore, MD (United States)

2015-06-15

Purpose: To evaluate weather the current radiobiological models can predict the normal liver complications of radioactive Yttrium-90 ({sup 90}Y) selective-internal-radiation-treatment (SIRT) for metastatic liver lesions based on the post-infusion {sup 90}Y PET images. Methods: A total of 20 patients with metastatic liver tumors treated with SIRT that received a post-infusion {sup 90}Y-PET/CT scan were analyzed in this work. The 3D activity distribution of the PET images was converted into a 3D dose distribution via a kernel convolution process. The physical dose distribution was converted into the equivalent dose (EQ2) delivered at 2 Gy based on the linear-quadratic (LQ) model considering the dose rate effect. The biological endpoint of this work was radiation-induce liver disease (RILD). The NTCPs were calculated with four different repair-times (T1/2-Liver-Repair= 0,0.5,1.0,2.0 hr) and three published NTCP models (Lyman-external-RT, Lyman 90Y-HCC-SIRT, parallel model) were compared to the incidence of RILD of the recruited patients to evaluate their ability of outcome prediction. Results: The mean normal liver physical dose (avg. 51.9 Gy, range 31.9–69.8 Gy) is higher than the suggested liver dose constraint for external beam treatment (∼30 Gy). However, none of the patients in our study developed RILD after the SIRT. The estimated probability of ‘no patient developing RILD’ obtained from the two Lyman models are 46.3% to 48.3% (T1/2-Liver-Repair= 0hr) and <1% for all other repair times. For the parallel model, the estimated probability is 97.3% (0hr), 51.7% (0.5hr), 2.0% (1.0hr) and <1% (2.0hr). Conclusion: Molecular-images providing the distribution of {sup 90}Y enable the dose-volume based dose/outcome analysis for SIRT. Current NTCP models fail to predict RILD complications in our patient population, unless a very short repair-time for the liver is assumed. The discrepancy between the Lyman {sup 90}Y-HCC-SIRT model predicted and the clinically

A statistical model for investigating binding probabilities of DNA nucleotide sequences using microarrays.

Science.gov (United States)

Lee, Mei-Ling Ting; Bulyk, Martha L; Whitmore, G A; Church, George M

2002-12-01

There is considerable scientific interest in knowing the probability that a site-specific transcription factor will bind to a given DNA sequence. Microarray methods provide an effective means for assessing the binding affinities of a large number of DNA sequences as demonstrated by Bulyk et al. (2001, Proceedings of the National Academy of Sciences, USA 98, 7158-7163) in their study of the DNA-binding specificities of Zif268 zinc fingers using microarray technology. In a follow-up investigation, Bulyk, Johnson, and Church (2002, Nucleic Acid Research 30, 1255-1261) studied the interdependence of nucleotides on the binding affinities of transcription proteins. Our article is motivated by this pair of studies. We present a general statistical methodology for analyzing microarray intensity measurements reflecting DNA-protein interactions. The log probability of a protein binding to a DNA sequence on an array is modeled using a linear ANOVA model. This model is convenient because it employs familiar statistical concepts and procedures and also because it is effective for investigating the probability structure of the binding mechanism.

Solving probability reasoning based on DNA strand displacement and probability modules.

Science.gov (United States)

Zhang, Qiang; Wang, Xiaobiao; Wang, Xiaojun; Zhou, Changjun

2017-12-01

In computation biology, DNA strand displacement technology is used to simulate the computation process and has shown strong computing ability. Most researchers use it to solve logic problems, but it is only rarely used in probabilistic reasoning. To process probabilistic reasoning, a conditional probability derivation model and total probability model based on DNA strand displacement were established in this paper. The models were assessed through the game "read your mind." It has been shown to enable the application of probabilistic reasoning in genetic diagnosis. Copyright © 2017 Elsevier Ltd. All rights reserved.

Estimating the Probability of Vegetation to Be Groundwater Dependent Based on the Evaluation of Tree Models

Directory of Open Access Journals (Sweden)

Isabel C. Pérez Hoyos

2016-04-01

Full Text Available Groundwater Dependent Ecosystems (GDEs are increasingly threatened by humans’ rising demand for water resources. Consequently, it is imperative to identify the location of GDEs to protect them. This paper develops a methodology to identify the probability of an ecosystem to be groundwater dependent. Probabilities are obtained by modeling the relationship between the known locations of GDEs and factors influencing groundwater dependence, namely water table depth and climatic aridity index. Probabilities are derived for the state of Nevada, USA, using modeled water table depth and aridity index values obtained from the Global Aridity database. The model selected results from the performance comparison of classification trees (CT and random forests (RF. Based on a threshold-independent accuracy measure, RF has a better ability to generate probability estimates. Considering a threshold that minimizes the misclassification rate for each model, RF also proves to be more accurate. Regarding training accuracy, performance measures such as accuracy, sensitivity, and specificity are higher for RF. For the test set, higher values of accuracy and kappa for CT highlight the fact that these measures are greatly affected by low prevalence. As shown for RF, the choice of the cutoff probability value has important consequences on model accuracy and the overall proportion of locations where GDEs are found.

Modelling detection probabilities to evaluate management and control tools for an invasive species

Science.gov (United States)

Christy, M.T.; Yackel Adams, A.A.; Rodda, G.H.; Savidge, J.A.; Tyrrell, C.L.

2010-01-01

For most ecologists, detection probability (p) is a nuisance variable that must be modelled to estimate the state variable of interest (i.e. survival, abundance, or occupancy). However, in the realm of invasive species control, the rate of detection and removal is the rate-limiting step for management of this pervasive environmental problem. For strategic planning of an eradication (removal of every individual), one must identify the least likely individual to be removed, and determine the probability of removing it. To evaluate visual searching as a control tool for populations of the invasive brown treesnake Boiga irregularis, we designed a mark-recapture study to evaluate detection probability as a function of time, gender, size, body condition, recent detection history, residency status, searcher team and environmental covariates. We evaluated these factors using 654 captures resulting from visual detections of 117 snakes residing in a 5-ha semi-forested enclosure on Guam, fenced to prevent immigration and emigration of snakes but not their prey. Visual detection probability was low overall (= 0??07 per occasion) but reached 0??18 under optimal circumstances. Our results supported sex-specific differences in detectability that were a quadratic function of size, with both small and large females having lower detection probabilities than males of those sizes. There was strong evidence for individual periodic changes in detectability of a few days duration, roughly doubling detection probability (comparing peak to non-elevated detections). Snakes in poor body condition had estimated mean detection probabilities greater than snakes with high body condition. Search teams with high average detection rates exhibited detection probabilities about twice that of search teams with low average detection rates. Surveys conducted with bright moonlight and strong wind gusts exhibited moderately decreased probabilities of detecting snakes. Synthesis and applications. By

Animal Models of Diabetic Macrovascular Complications: Key Players in the Development of New Therapeutic Approaches

Directory of Open Access Journals (Sweden)

Suvi E. Heinonen

2015-01-01

Full Text Available Diabetes mellitus is a lifelong, incapacitating metabolic disease associated with chronic macrovascular complications (coronary heart disease, stroke, and peripheral vascular disease and microvascular disorders leading to damage of the kidneys (nephropathy and eyes (retinopathy. Based on the current trends, the rising prevalence of diabetes worldwide will lead to increased cardiovascular morbidity and mortality. Therefore, novel means to prevent and treat these complications are needed. Under the auspices of the IMI (Innovative Medicines Initiative, the SUMMIT (SUrrogate markers for Micro- and Macrovascular hard end points for Innovative diabetes Tools consortium is working on the development of novel animal models that better replicate vascular complications of diabetes and on the characterization of the available models. In the past years, with the high level of genomic information available and more advanced molecular tools, a very large number of models has been created. Selecting the right model for a specific study is not a trivial task and will have an impact on the study results and their interpretation. This review gathers information on the available experimental animal models of diabetic macrovascular complications and evaluates their pros and cons for research purposes as well as for drug development.

Probabilities in physics

CERN Document Server

Hartmann, Stephan

2011-01-01

Many results of modern physics--those of quantum mechanics, for instance--come in a probabilistic guise. But what do probabilistic statements in physics mean? Are probabilities matters of objective fact and part of the furniture of the world, as objectivists think? Or do they only express ignorance or belief, as Bayesians suggest? And how are probabilistic hypotheses justified and supported by empirical evidence? Finally, what does the probabilistic nature of physics imply for our understanding of the world? This volume is the first to provide a philosophical appraisal of probabilities in all of physics. Its main aim is to make sense of probabilistic statements as they occur in the various physical theories and models and to provide a plausible epistemology and metaphysics of probabilities. The essays collected here consider statistical physics, probabilistic modelling, and quantum mechanics, and critically assess the merits and disadvantages of objectivist and subjectivist views of probabilities in these fie...

Ruin probabilities

DEFF Research Database (Denmark)

Asmussen, Søren; Albrecher, Hansjörg

The book gives a comprehensive treatment of the classical and modern ruin probability theory. Some of the topics are Lundberg's inequality, the Cramér-Lundberg approximation, exact solutions, other approximations (e.g., for heavy-tailed claim size distributions), finite horizon ruin probabilities......, extensions of the classical compound Poisson model to allow for reserve-dependent premiums, Markov-modulation, periodicity, change of measure techniques, phase-type distributions as a computational vehicle and the connection to other applied probability areas, like queueing theory. In this substantially...... updated and extended second version, new topics include stochastic control, fluctuation theory for Levy processes, Gerber–Shiu functions and dependence....

Modeling highway travel time distribution with conditional probability models

Energy Technology Data Exchange (ETDEWEB)

Oliveira Neto, Francisco Moraes [ORNL; Chin, Shih-Miao [ORNL; Hwang, Ho-Ling [ORNL; Han, Lee [University of Tennessee, Knoxville (UTK)

2014-01-01

ABSTRACT Under the sponsorship of the Federal Highway Administration's Office of Freight Management and Operations, the American Transportation Research Institute (ATRI) has developed performance measures through the Freight Performance Measures (FPM) initiative. Under this program, travel speed information is derived from data collected using wireless based global positioning systems. These telemetric data systems are subscribed and used by trucking industry as an operations management tool. More than one telemetric operator submits their data dumps to ATRI on a regular basis. Each data transmission contains truck location, its travel time, and a clock time/date stamp. Data from the FPM program provides a unique opportunity for studying the upstream-downstream speed distributions at different locations, as well as different time of the day and day of the week. This research is focused on the stochastic nature of successive link travel speed data on the continental United States Interstates network. Specifically, a method to estimate route probability distributions of travel time is proposed. This method uses the concepts of convolution of probability distributions and bivariate, link-to-link, conditional probability to estimate the expected distributions for the route travel time. Major contribution of this study is the consideration of speed correlation between upstream and downstream contiguous Interstate segments through conditional probability. The established conditional probability distributions, between successive segments, can be used to provide travel time reliability measures. This study also suggests an adaptive method for calculating and updating route travel time distribution as new data or information is added. This methodology can be useful to estimate performance measures as required by the recent Moving Ahead for Progress in the 21st Century Act (MAP 21).

Application of damping mechanism model and stacking fault probability in Fe-Mn alloy

International Nuclear Information System (INIS)

Huang, S.K.; Wen, Y.H.; Li, N.; Teng, J.; Ding, S.; Xu, Y.G.

2008-01-01

In this paper, the damping mechanism model of Fe-Mn alloy was analyzed using dislocation theory. Moreover, as an important parameter in Fe-Mn based alloy, the effect of stacking fault probability on the damping capacity of Fe-19.35Mn alloy after deep-cooling or tensile deformation was also studied. The damping capacity was measured using reversal torsion pendulum. The stacking fault probability of γ-austenite and ε-martensite was determined by means of X-ray diffraction (XRD) profile analysis. The microstructure was observed using scanning electronic microscope (SEM). The results indicated that with the strain amplitude increasing above a critical value, the damping capacity of Fe-19.35Mn alloy increased rapidly which could be explained using the breakaway model of Shockley partial dislocations. Deep-cooling and suitable tensile deformation could improve the damping capacity owning to the increasing of stacking fault probability of Fe-19.35Mn alloy

Choice probability generating functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

2010-01-01

This paper establishes that every random utility discrete choice model (RUM) has a representation that can be characterized by a choice-probability generating function (CPGF) with specific properties, and that every function with these specific properties is consistent with a RUM. The choice...... probabilities from the RUM are obtained from the gradient of the CPGF. Mixtures of RUM are characterized by logarithmic mixtures of their associated CPGF. The paper relates CPGF to multivariate extreme value distributions, and reviews and extends methods for constructing generating functions for applications....... The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended to competing risk survival models....

Comparison of prospective risk estimates for postoperative complications: human vs computer model.

Science.gov (United States)

Glasgow, Robert E; Hawn, Mary T; Hosokawa, Patrick W; Henderson, William G; Min, Sung-Joon; Richman, Joshua S; Tomeh, Majed G; Campbell, Darrell; Neumayer, Leigh A

2014-02-01

Surgical quality improvement tools such as NSQIP are limited in their ability to prospectively affect individual patient care by the retrospective audit and feedback nature of their design. We hypothesized that statistical models using patient preoperative characteristics could prospectively provide risk estimates of postoperative adverse events comparable to risk estimates provided by experienced surgeons, and could be useful for stratifying preoperative assessment of patient risk. This was a prospective observational cohort. Using previously developed models for 30-day postoperative mortality, overall morbidity, cardiac, thromboembolic, pulmonary, renal, and surgical site infection (SSI) complications, model and surgeon estimates of risk were compared with each other and with actual 30-day outcomes. The study cohort included 1,791 general surgery patients operated on between June 2010 and January 2012. Observed outcomes were mortality (0.2%), overall morbidity (8.2%), and pulmonary (1.3%), cardiac (0.3%), thromboembolism (0.2%), renal (0.4%), and SSI (3.8%) complications. Model and surgeon risk estimates showed significant correlation (p risk for overall morbidity to be low, the model-predicted risk and observed morbidity rates were 2.8% and 4.1%, respectively, compared with 10% and 18% in perceived high risk patients. Patients in the highest quartile of model-predicted risk accounted for 75% of observed mortality and 52% of morbidity. Across a broad range of general surgical operations, we confirmed that the model risk estimates are in fairly good agreement with risk estimates of experienced surgeons. Using these models prospectively can identify patients at high risk for morbidity and mortality, who could then be targeted for intervention to reduce postoperative complications. Published by Elsevier Inc.

On the Probability of Occurrence of Clusters in Abelian Sandpile Model

OpenAIRE

Moradi, M.; Rouhani, S.

2004-01-01

We have performed extensive simulations on the Abelian Sandpile Model (ASM) on square lattice. We have estimated the probability of observation of many clusters. Some are in good agreement with previous analytical results, while some show discrepancies between simulation and analytical results.

Assessment of different models for computing the probability of a clear line of sight

Science.gov (United States)

Bojin, Sorin; Paulescu, Marius; Badescu, Viorel

2017-12-01

This paper is focused on modeling the morphological properties of the cloud fields in terms of the probability of a clear line of sight (PCLOS). PCLOS is defined as the probability that a line of sight between observer and a given point of the celestial vault goes freely without intersecting a cloud. A variety of PCLOS models assuming the cloud shape hemisphere, semi-ellipsoid and ellipsoid are tested. The effective parameters (cloud aspect ratio and absolute cloud fraction) are extracted from high-resolution series of sunshine number measurements. The performance of the PCLOS models is evaluated from the perspective of their ability in retrieving the point cloudiness. The advantages and disadvantages of the tested models are discussed, aiming to a simplified parameterization of PCLOS models.

Human Inferences about Sequences: A Minimal Transition Probability Model.

Directory of Open Access Journals (Sweden)

Florent Meyniel

2016-12-01

Full Text Available The brain constantly infers the causes of the inputs it receives and uses these inferences to generate statistical expectations about future observations. Experimental evidence for these expectations and their violations include explicit reports, sequential effects on reaction times, and mismatch or surprise signals recorded in electrophysiology and functional MRI. Here, we explore the hypothesis that the brain acts as a near-optimal inference device that constantly attempts to infer the time-varying matrix of transition probabilities between the stimuli it receives, even when those stimuli are in fact fully unpredictable. This parsimonious Bayesian model, with a single free parameter, accounts for a broad range of findings on surprise signals, sequential effects and the perception of randomness. Notably, it explains the pervasive asymmetry between repetitions and alternations encountered in those studies. Our analysis suggests that a neural machinery for inferring transition probabilities lies at the core of human sequence knowledge.

An extended car-following model considering the appearing probability of truck and driver's characteristics

Science.gov (United States)

Rong, Ying; Wen, Huiying

2018-05-01

In this paper, the appearing probability of truck is introduced and an extended car-following model is presented to analyze the traffic flow based on the consideration of driver's characteristics, under honk environment. The stability condition of this proposed model is obtained through linear stability analysis. In order to study the evolution properties of traffic wave near the critical point, the mKdV equation is derived by the reductive perturbation method. The results show that the traffic flow will become more disorder for the larger appearing probability of truck. Besides, the appearance of leading truck affects not only the stability of traffic flow, but also the effect of other aspects on traffic flow, such as: driver's reaction and honk effect. The effects of them on traffic flow are closely correlated with the appearing probability of truck. Finally, the numerical simulations under the periodic boundary condition are carried out to verify the proposed model. And they are consistent with the theoretical findings.

Probability Model for Data Redundancy Detection in Sensor Networks

Directory of Open Access Journals (Sweden)

Suman Kumar

2009-01-01

Full Text Available Sensor networks are made of autonomous devices that are able to collect, store, process and share data with other devices. Large sensor networks are often redundant in the sense that the measurements of some nodes can be substituted by other nodes with a certain degree of confidence. This spatial correlation results in wastage of link bandwidth and energy. In this paper, a model for two associated Poisson processes, through which sensors are distributed in a plane, is derived. A probability condition is established for data redundancy among closely located sensor nodes. The model generates a spatial bivariate Poisson process whose parameters depend on the parameters of the two individual Poisson processes and on the distance between the associated points. The proposed model helps in building efficient algorithms for data dissemination in the sensor network. A numerical example is provided investigating the advantage of this model.

Pulmonary Complications Resulting from Genetic Cardiovascular Disease in Two Rat Models

Science.gov (United States)

Underlying cardiovascular disease (CVD) has been considered a risk factor for exacerbation of air pollution health effects. Therefore, rodent models of CVD are increasingly used to examine mechanisms of variation in susceptibility. Pulmonary complications and altered iron homeost...

A nonaxial boost may reduce late complications of radiotherapy for prostate cancer

Energy Technology Data Exchange (ETDEWEB)

Ben-Josef, E; Mesina, C F; Choi, J; Forman, J D

1995-07-01

Purpose: The nonaxial external beam (NAEBT) prostate boost technique was designed to reduce late complications of radiotherapy for prostate cancer. It has been previously shown that with this beam arrangement, the volumes of bladder and rectum receiving high doses could be substantially reduced. This study was undertaken to find if these advantages in dose distribution would translate into clinically significant benefits. Materials and Methods: Follow-up was obtained on 106 prostate cancer patients who had been treated with 3D conformal radiotherapy. Late complications were scored using the RTOG scale. A standard four-field axial (STD) technique had been used to deliver 45 Gy to the prostate, seminal vesicles and periprostatic lymph-nodes. A subsequent 24 Gy boost had been delivered using a STD technique (58 patients) or a NAEBT technique (48 patients). In the latter, the opposing anterior and posterior pair of beams had been substituted for a right and left anterior infero-superior pair. Actuarial probabilities of developing late complications were calculated by the life-table method. The Mantel-Haenszel test was used to compare these probabilities between the two groups. Results: The groups were comparable in regard to age, race, pretreatment serum PSA, stage distribution and dose to prostate. With a median follow-up of 21 months, 18 patients have developed grade 1-2 gastrointestinal or genitourinary complications (14 in the STD group, 4 in the NAEBT group). There were no grade 3-4 complications. The actuarial 3-year complication probability was 58% and 11% in the STD and NAEBT groups, respectively. However, this difference was not statistically significant. Gastrointestinal and genitourinary complications were reduced from 12.1% to 6.2% and from 15.5% to 4.2%, respectively. Conclusion: The use of a nonaxial boost technique has resulted in fewer complications in patients treated with 3D conformal radiotherapy for localized prostate cancer. The greater reduction

Survival modeling for the estimation of transition probabilities in model-based economic evaluations in the absence of individual patient data: a tutorial.

Science.gov (United States)

Diaby, Vakaramoko; Adunlin, Georges; Montero, Alberto J

2014-02-01

Survival modeling techniques are increasingly being used as part of decision modeling for health economic evaluations. As many models are available, it is imperative for interested readers to know about the steps in selecting and using the most suitable ones. The objective of this paper is to propose a tutorial for the application of appropriate survival modeling techniques to estimate transition probabilities, for use in model-based economic evaluations, in the absence of individual patient data (IPD). An illustration of the use of the tutorial is provided based on the final progression-free survival (PFS) analysis of the BOLERO-2 trial in metastatic breast cancer (mBC). An algorithm was adopted from Guyot and colleagues, and was then run in the statistical package R to reconstruct IPD, based on the final PFS analysis of the BOLERO-2 trial. It should be emphasized that the reconstructed IPD represent an approximation of the original data. Afterwards, we fitted parametric models to the reconstructed IPD in the statistical package Stata. Both statistical and graphical tests were conducted to verify the relative and absolute validity of the findings. Finally, the equations for transition probabilities were derived using the general equation for transition probabilities used in model-based economic evaluations, and the parameters were estimated from fitted distributions. The results of the application of the tutorial suggest that the log-logistic model best fits the reconstructed data from the latest published Kaplan-Meier (KM) curves of the BOLERO-2 trial. Results from the regression analyses were confirmed graphically. An equation for transition probabilities was obtained for each arm of the BOLERO-2 trial. In this paper, a tutorial was proposed and used to estimate the transition probabilities for model-based economic evaluation, based on the results of the final PFS analysis of the BOLERO-2 trial in mBC. The results of our study can serve as a basis for any model

Dependence in probabilistic modeling Dempster-Shafer theory and probability bounds analysis

Energy Technology Data Exchange (ETDEWEB)

Ferson, Scott [Applied Biomathematics, Setauket, NY (United States); Nelsen, Roger B. [Lewis & Clark College, Portland OR (United States); Hajagos, Janos [Applied Biomathematics, Setauket, NY (United States); Berleant, Daniel J. [Iowa State Univ., Ames, IA (United States); Zhang, Jianzhong [Iowa State Univ., Ames, IA (United States); Tucker, W. Troy [Applied Biomathematics, Setauket, NY (United States); Ginzburg, Lev R. [Applied Biomathematics, Setauket, NY (United States); Oberkampf, William L. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2015-05-01

This report summarizes methods to incorporate information (or lack of information) about inter-variable dependence into risk assessments that use Dempster-Shafer theory or probability bounds analysis to address epistemic and aleatory uncertainty. The report reviews techniques for simulating correlated variates for a given correlation measure and dependence model, computation of bounds on distribution functions under a specified dependence model, formulation of parametric and empirical dependence models, and bounding approaches that can be used when information about the intervariable dependence is incomplete. The report also reviews several of the most pervasive and dangerous myths among risk analysts about dependence in probabilistic models.

CT findings of acute cholecystitis and its complications.

Science.gov (United States)

Shakespear, Jonathan S; Shaaban, Akram M; Rezvani, Maryam

2010-06-01

The purpose of this article is to describe and illustrate the CT findings of acute cholecystitis and its complications. CT findings suggesting acute cholecystitis should be interpreted with caution and should probably serve as justification for further investigation with abdominal ultrasound. CT has a relatively high negative predictive value, and acute cholecystitis is unlikely in the setting of a negative CT. Complications of acute cholecystitis have a characteristic CT appearance and include necrosis, perforation, abscess formation, intraluminal hemorrhage, and wall emphysema.

Complications of acromegaly: thyroid and colon.

Science.gov (United States)

Tirosh, Amit; Shimon, Ilan

2017-02-01

In acromegaly the long-term exposure to high growth hormone (GH) and insulin-like growth factor-1 (IGF-1) levels may result in specific complications in different human organs, including the thyroid gland and the colon. We will review here the evidence available regarding the characteristic thyroid and colon complications in acromegaly. This review summarizes the published data observing noncancerous structural abnormalities (thyroid nodules, colonic polyps) and thyroid and colon cancer in patients diagnosed with acromegaly. Thyroid micro-carcinomas are probably over-diagnosed among acromegalic patients. In regard to colon cancer, there is no sufficient data to suggest that colon cancer risk is higher in acromegaly compared to the general population.

Predicting critical transitions in dynamical systems from time series using nonstationary probability density modeling.

Science.gov (United States)

Kwasniok, Frank

2013-11-01

A time series analysis method for predicting the probability density of a dynamical system is proposed. A nonstationary parametric model of the probability density is estimated from data within a maximum likelihood framework and then extrapolated to forecast the future probability density and explore the system for critical transitions or tipping points. A full systematic account of parameter uncertainty is taken. The technique is generic, independent of the underlying dynamics of the system. The method is verified on simulated data and then applied to prediction of Arctic sea-ice extent.

Robust mislabel logistic regression without modeling mislabel probabilities.

Science.gov (United States)

Hung, Hung; Jou, Zhi-Yu; Huang, Su-Yun

2018-03-01

Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting a conventional logistic regression can then lead to biased estimation. One common resolution is to fit a mislabel logistic regression model, which takes into consideration of mislabeled responses. Another common method is to adopt a robust M-estimation by down-weighting suspected instances. In this work, we propose a new robust mislabel logistic regression based on γ-divergence. Our proposal possesses two advantageous features: (1) It does not need to model the mislabel probabilities. (2) The minimum γ-divergence estimation leads to a weighted estimating equation without the need to include any bias correction term, that is, it is automatically bias-corrected. These features make the proposed γ-logistic regression more robust in model fitting and more intuitive for model interpretation through a simple weighting scheme. Our method is also easy to implement, and two types of algorithms are included. Simulation studies and the Pima data application are presented to demonstrate the performance of γ-logistic regression. © 2017, The International Biometric Society.

Posterior Probability Matching and Human Perceptual Decision Making.

Directory of Open Access Journals (Sweden)

Richard F Murray

2015-06-01

Full Text Available Probability matching is a classic theory of decision making that was first developed in models of cognition. Posterior probability matching, a variant in which observers match their response probabilities to the posterior probability of each response being correct, is being used increasingly often in models of perception. However, little is known about whether posterior probability matching is consistent with the vast literature on vision and hearing that has developed within signal detection theory. Here we test posterior probability matching models using two tools from detection theory. First, we examine the models' performance in a two-pass experiment, where each block of trials is presented twice, and we measure the proportion of times that the model gives the same response twice to repeated stimuli. We show that at low performance levels, posterior probability matching models give highly inconsistent responses across repeated presentations of identical trials. We find that practised human observers are more consistent across repeated trials than these models predict, and we find some evidence that less practised observers more consistent as well. Second, we compare the performance of posterior probability matching models on a discrimination task to the performance of a theoretical ideal observer that achieves the best possible performance. We find that posterior probability matching is very inefficient at low-to-moderate performance levels, and that human observers can be more efficient than is ever possible according to posterior probability matching models. These findings support classic signal detection models, and rule out a broad class of posterior probability matching models for expert performance on perceptual tasks that range in complexity from contrast discrimination to symmetry detection. However, our findings leave open the possibility that inexperienced observers may show posterior probability matching behaviour, and our methods

A COMPLICATED GRIEF INTERVENTION MODEL

African Journals Online (AJOL)

2010-07-29

Jul 29, 2010 ... of complicated grief as a contributing factor to impaired social functioning. This can ... includes a diagnosis of bereavement-related major depression if symptoms ..... networking, Social Sciences Citation Index, Social Sciences.

Increase in tumor control and normal tissue complication probabilities in advanced head-and-neck cancer for dose-escalated intensity-modulated photon and proton therapy

Directory of Open Access Journals (Sweden)

Annika eJakobi

2015-11-01

Full Text Available Introduction:Presently used radio-chemotherapy regimens result in moderate local control rates for patients with advanced head and neck squamous cell carcinoma (HNSCC. Dose escalation (DE may be an option to improve patient outcome, but may also increase the risk of toxicities in healthy tissue. The presented treatment planning study evaluated the feasibility of two DE levels for advanced HNSCC patients, planned with either intensity-modulated photon therapy (IMXT or proton therapy (IMPT.Materials and Methods:For 45 HNSCC patients, IMXT and IMPT treatment plans were created including DE via a simultaneous integrated boost (SIB in the high-risk volume, while maintaining standard fractionation with 2 Gy per fraction in the remaining target volume. Two DE levels for the SIB were compared: 2.3 Gy and 2.6 Gy. Treatment plan evaluation included assessment of tumor control probabilities (TCP and normal tissue complication probabilities (NTCP.Results:An increase of approximately 10% in TCP was estimated between the DE levels. A pronounced high-dose rim surrounding the SIB volume was identified in IMXT treatment. Compared to IMPT, this extra dose slightly increased the TCP values and to a larger extent the NTCP values. For both modalities, the higher DE level led only to a small increase in NTCP values (mean differences < 2% in all models, except for the risk of aspiration, which increased on average by 8% and 6% with IMXT and IMPT, respectively, but showed a considerable patient dependence. Conclusions:Both DE levels appear applicable to patients with IMXT and IMPT since all calculated NTCP values, except for one, increased only little for the higher DE level. The estimated TCP increase is of relevant magnitude. The higher DE schedule needs to be investigated carefully in the setting of a prospective clinical trial, especially regarding toxicities caused by high local doses that lack a sound dose response description, e.g., ulcers.

Smoking, Labor, & Delivery: It's Complicated

Science.gov (United States)

You probably have mixed feelings about going into labor. On one hand, bringing a new life into the world is really exciting. On the other, it can be really scary to have a baby, especially if this is your first child. Unfortunately, it can be even scarier if you smoke. Research shows that smoking during pregnancy can lead to serious complications for you and your baby during labor and delivery.

The perception of probability.

Science.gov (United States)

Gallistel, C R; Krishan, Monika; Liu, Ye; Miller, Reilly; Latham, Peter E

2014-01-01

We present a computational model to explain the results from experiments in which subjects estimate the hidden probability parameter of a stepwise nonstationary Bernoulli process outcome by outcome. The model captures the following results qualitatively and quantitatively, with only 2 free parameters: (a) Subjects do not update their estimate after each outcome; they step from one estimate to another at irregular intervals. (b) The joint distribution of step widths and heights cannot be explained on the assumption that a threshold amount of change must be exceeded in order for them to indicate a change in their perception. (c) The mapping of observed probability to the median perceived probability is the identity function over the full range of probabilities. (d) Precision (how close estimates are to the best possible estimate) is good and constant over the full range. (e) Subjects quickly detect substantial changes in the hidden probability parameter. (f) The perceived probability sometimes changes dramatically from one observation to the next. (g) Subjects sometimes have second thoughts about a previous change perception, after observing further outcomes. (h) The frequency with which they perceive changes moves in the direction of the true frequency over sessions. (Explaining this finding requires 2 additional parametric assumptions.) The model treats the perception of the current probability as a by-product of the construction of a compact encoding of the experienced sequence in terms of its change points. It illustrates the why and the how of intermittent Bayesian belief updating and retrospective revision in simple perception. It suggests a reinterpretation of findings in the recent literature on the neurobiology of decision making. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

An analytical calculation of neighbourhood order probabilities for high dimensional Poissonian processes and mean field models

International Nuclear Information System (INIS)

Tercariol, Cesar Augusto Sangaletti; Kiipper, Felipe de Moura; Martinez, Alexandre Souto

2007-01-01

Consider that the coordinates of N points are randomly generated along the edges of a d-dimensional hypercube (random point problem). The probability P (d,N) m,n that an arbitrary point is the mth nearest neighbour to its own nth nearest neighbour (Cox probabilities) plays an important role in spatial statistics. Also, it has been useful in the description of physical processes in disordered media. Here we propose a simpler derivation of Cox probabilities, where we stress the role played by the system dimensionality d. In the limit d → ∞, the distances between pair of points become independent (random link model) and closed analytical forms for the neighbourhood probabilities are obtained both for the thermodynamic limit and finite-size system. Breaking the distance symmetry constraint drives us to the random map model, for which the Cox probabilities are obtained for two cases: whether a point is its own nearest neighbour or not

On new cautious structural reliability models in the framework of imprecise probabilities

DEFF Research Database (Denmark)

Utkin, Lev; Kozine, Igor

2010-01-01

measures when the number of events of interest or observations is very small. The main feature of the models is that prior ignorance is not modelled by a fixed single prior distribution, but by a class of priors which is defined by upper and lower probabilities that can converge as statistical data......New imprecise structural reliability models are described in this paper. They are developed based on the imprecise Bayesian inference and are imprecise Dirichlet, imprecise negative binomial, gamma-exponential and normal models. The models are applied to computing cautious structural reliability...

Modeling Stochastic Complexity in Complex Adaptive Systems: Non-Kolmogorov Probability and the Process Algebra Approach.

Science.gov (United States)

Sulis, William H

2017-10-01

Walter Freeman III pioneered the application of nonlinear dynamical systems theories and methodologies in his work on mesoscopic brain dynamics.Sadly, mainstream psychology and psychiatry still cling to linear correlation based data analysis techniques, which threaten to subvert the process of experimentation and theory building. In order to progress, it is necessary to develop tools capable of managing the stochastic complexity of complex biopsychosocial systems, which includes multilevel feedback relationships, nonlinear interactions, chaotic dynamics and adaptability. In addition, however, these systems exhibit intrinsic randomness, non-Gaussian probability distributions, non-stationarity, contextuality, and non-Kolmogorov probabilities, as well as the absence of mean and/or variance and conditional probabilities. These properties and their implications for statistical analysis are discussed. An alternative approach, the Process Algebra approach, is described. It is a generative model, capable of generating non-Kolmogorov probabilities. It has proven useful in addressing fundamental problems in quantum mechanics and in the modeling of developing psychosocial systems.

Choice probability generating functions

DEFF Research Database (Denmark)

Fosgerau, Mogens; McFadden, Daniel; Bierlaire, Michel

2013-01-01

This paper considers discrete choice, with choice probabilities coming from maximization of preferences from a random utility field perturbed by additive location shifters (ARUM). Any ARUM can be characterized by a choice-probability generating function (CPGF) whose gradient gives the choice...... probabilities, and every CPGF is consistent with an ARUM. We relate CPGF to multivariate extreme value distributions, and review and extend methods for constructing CPGF for applications. The choice probabilities of any ARUM may be approximated by a cross-nested logit model. The results for ARUM are extended...

Complications of cranioplasty after decompressive craniectomy

Directory of Open Access Journals (Sweden)

Maša Glišović

2015-04-01

Full Text Available Cranioplasty is a surgical repair of a defect or deformity of a skull with the use of autologous bone or synthetic materials.[4] It usually follows decompressive craniectomy, which is a commonly practiced neurosurgical intervention in patients with raised intracranial pressure unresponsive to other forms of treatment.[1] There are many conditions that may lead to intracranial hypertension, and the goal is to avoid brain necrosis caused by compartment pressure syndrome.[2] Consequently, the extensive use of decompressive craniectomy directly results in more cranioplasties, which sometimes present with unwanted complications.[5] Generally, the occurence of cranioplasty complications is between 16% and 34%.[3] Because of the many indications for craniectomy based on clinical data that speak in its favour, if will probably remain a relatively common neurosurgical intervention also in the future. The frequency of decompressive craniectomy and consequently of cranioplasty requires awareness of the many potential postoperative complications and understanding of its evolution. This article is a review of pathophysiological mechanisms after decompressive craniectomy and cranioplasty, of its complications and factors that potentially contribute to their occurence.

Transition probabilities of health states for workers in Malaysia using a Markov chain model

Science.gov (United States)

Samsuddin, Shamshimah; Ismail, Noriszura

2017-04-01

The aim of our study is to estimate the transition probabilities of health states for workers in Malaysia who contribute to the Employment Injury Scheme under the Social Security Organization Malaysia using the Markov chain model. Our study uses four states of health (active, temporary disability, permanent disability and death) based on the data collected from the longitudinal studies of workers in Malaysia for 5 years. The transition probabilities vary by health state, age and gender. The results show that men employees are more likely to have higher transition probabilities to any health state compared to women employees. The transition probabilities can be used to predict the future health of workers in terms of a function of current age, gender and health state.

Estimation and prediction of maximum daily rainfall at Sagar Island using best fit probability models

Science.gov (United States)

Mandal, S.; Choudhury, B. U.

2015-07-01

Sagar Island, setting on the continental shelf of Bay of Bengal, is one of the most vulnerable deltas to the occurrence of extreme rainfall-driven climatic hazards. Information on probability of occurrence of maximum daily rainfall will be useful in devising risk management for sustaining rainfed agrarian economy vis-a-vis food and livelihood security. Using six probability distribution models and long-term (1982-2010) daily rainfall data, we studied the probability of occurrence of annual, seasonal and monthly maximum daily rainfall (MDR) in the island. To select the best fit distribution models for annual, seasonal and monthly time series based on maximum rank with minimum value of test statistics, three statistical goodness of fit tests, viz. Kolmogorove-Smirnov test (K-S), Anderson Darling test ( A 2 ) and Chi-Square test ( X 2) were employed. The fourth probability distribution was identified from the highest overall score obtained from the three goodness of fit tests. Results revealed that normal probability distribution was best fitted for annual, post-monsoon and summer seasons MDR, while Lognormal, Weibull and Pearson 5 were best fitted for pre-monsoon, monsoon and winter seasons, respectively. The estimated annual MDR were 50, 69, 86, 106 and 114 mm for return periods of 2, 5, 10, 20 and 25 years, respectively. The probability of getting an annual MDR of >50, >100, >150, >200 and >250 mm were estimated as 99, 85, 40, 12 and 03 % level of exceedance, respectively. The monsoon, summer and winter seasons exhibited comparatively higher probabilities (78 to 85 %) for MDR of >100 mm and moderate probabilities (37 to 46 %) for >150 mm. For different recurrence intervals, the percent probability of MDR varied widely across intra- and inter-annual periods. In the island, rainfall anomaly can pose a climatic threat to the sustainability of agricultural production and thus needs adequate adaptation and mitigation measures.

Probability-based collaborative filtering model for predicting gene–disease associations

OpenAIRE

Zeng, Xiangxiang; Ding, Ningxiang; Rodríguez-Patón, Alfonso; Zou, Quan

2017-01-01

Background Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene–disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. Methods We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our mo...

Development of a new model to evaluate the probability of automatic plant trips for pressurized water reactors

Energy Technology Data Exchange (ETDEWEB)

Shimada, Yoshio [Institute of Nuclear Safety System Inc., Mihama, Fukui (Japan); Kawai, Katsunori; Suzuki, Hiroshi [Mitsubishi Heavy Industries Ltd., Tokyo (Japan)

2001-09-01

In order to improve the reliability of plant operations for pressurized water reactors, a new fault tree model was developed to evaluate the probability of automatic plant trips. This model consists of fault trees for sixteen systems. It has the following features: (1) human errors and transmission line incidents are modeled by the existing data, (2) the repair of failed components is considered to calculate the failure probability of components, (3) uncertainty analysis is performed by an exact method. From the present results, it is confirmed that the obtained upper and lower bound values of the automatic plant trip probability are within the existing data bound in Japan. Thereby this model can be applicable to the prediction of plant performance and reliability. (author)

Predicting Flow Breakdown Probability and Duration in Stochastic Network Models: Impact on Travel Time Reliability

Energy Technology Data Exchange (ETDEWEB)

Dong, Jing [ORNL; Mahmassani, Hani S. [Northwestern University, Evanston

2011-01-01

This paper proposes a methodology to produce random flow breakdown endogenously in a mesoscopic operational model, by capturing breakdown probability and duration. Based on previous research findings that probability of flow breakdown can be represented as a function of flow rate and the duration can be characterized by a hazard model. By generating random flow breakdown at various levels and capturing the traffic characteristics at the onset of the breakdown, the stochastic network simulation model provides a tool for evaluating travel time variability. The proposed model can be used for (1) providing reliability related traveler information; (2) designing ITS (intelligent transportation systems) strategies to improve reliability; and (3) evaluating reliability-related performance measures of the system.

Pre-Service Mathematics Teachers' Use of Probability Models in Making Informal Inferences about a Chance Game

Science.gov (United States)

Kazak, Sibel; Pratt, Dave

2017-01-01

This study considers probability models as tools for both making informal statistical inferences and building stronger conceptual connections between data and chance topics in teaching statistics. In this paper, we aim to explore pre-service mathematics teachers' use of probability models for a chance game, where the sum of two dice matters in…

Impact of neoadjuvant chemotherapy on complications of minimally invasive radical cystectomy.

Science.gov (United States)

Lizée, D; Salas, R S; Barret, E; Galiano, M; Di Trapani, E; Montorsi, F; Cathelineau, X

2017-03-01

Neoadjuvant chemotherapy (NC) before minimally invasive radical cystectomy (MIRC) is considered a standard of care in muscle-invasive bladder cancer or recurrent high-risk non-muscle-invasive bladder cancer. To evaluate the impact of NC on morbidity and mortality after MIRC. We prospectively evaluated 135 patients who underwent MIRC (laparoscopic: n=100; robotic: n=35) between 2007 and 2013 with ≥90 days of follow-up (median age: 66 year). Complications were analyzed and graded according to the Clavien Dindo classification system. Logistic regression models were used to evaluate the impact of NC on postoperative complications. Kaplan-Meier methods with the log-rank test were used for cancer-specific survival probabilities and differences between the 2groups (MIRC with and without NC). Sixty-two of 135 patients received NC. A total of 118 patients (87.4%) developed 179 complications, chiefly infectious (48.0%) or gastrointestinal (21.2%), ≤90 days after surgery; 3 patients died bladder cancer who had NC versus no NC. We did not find any significant differences in terms of early or late complications, length of stay, or reintervention. The oncologic outcomes regarding NC were encouraging. Copyright © 2016. Publicado por Elsevier España, S.L.U.

Continuum shell-model with complicated configurations

International Nuclear Information System (INIS)

Barz, H.W.; Hoehn, J.

1977-05-01

The traditional shell model has been combined with the coupled channels method in order to describe resonance reactions. For that purpose the configuration space is divided into two subspaces (Feshbach projection method). Complicated shell-model configurations can be included into the subspace of discrete states which contains the single particle resonance states too. In the subspace of scattering states the equation of motion is solved by using the coupled channels method. Thereby the orthogonality between scattering states and discrete states is ensured. Resonance states are defined with outgoing waves in all channels. By means of simple model calculations the special role of the continuum is investigated. In this connection the energy dependence of the resonance parameters, the isospin mixture via the continuum, threshold effect, as well as the influence of the number of channels taken into account on the widths, positions and dipole strengths of the resonance are discussed. The model is mainly applied to the description of giant resonances excited by the scattering of nucleons and photo-nucleus processes (source term method) found in reactions on light nuclei. The giant resonance observed in the 15 N(p,n) reaction is explained by the inclusion of 2p-2h states. The same is true for the giant resonance in 13 C(J = 1/2, 3/2) as well as for the giant resonance built on the first 3 - state in 16 O. By means of a correlation analysis for the reduced widths amplitudes an access to the doorway conception is found. (author)

Exploring the Subtleties of Inverse Probability Weighting and Marginal Structural Models.

Science.gov (United States)

Breskin, Alexander; Cole, Stephen R; Westreich, Daniel

2018-05-01

Since being introduced to epidemiology in 2000, marginal structural models have become a commonly used method for causal inference in a wide range of epidemiologic settings. In this brief report, we aim to explore three subtleties of marginal structural models. First, we distinguish marginal structural models from the inverse probability weighting estimator, and we emphasize that marginal structural models are not only for longitudinal exposures. Second, we explore the meaning of the word "marginal" in "marginal structural model." Finally, we show that the specification of a marginal structural model can have important implications for the interpretation of its parameters. Each of these concepts have important implications for the use and understanding of marginal structural models, and thus providing detailed explanations of them may lead to better practices for the field of epidemiology.

Zebrafish as a Model for the Study of Microvascular Complications of Diabetes and Their Mechanisms

Directory of Open Access Journals (Sweden)

Karl Heckler

2017-09-01

Full Text Available Diabetes mellitus (DM is a crucial metabolic disease that leads to severe disorders. These include macrovascular complications such as myocardial infarction, stroke, and peripheral artery disease and microvascular complications including diabetic nephropathy, neuropathy, and retinopathy. Diabetes mellitus, along with its associated organ pathologies, is one of the key problems in today’s medicine. Zebrafish is an upcoming disease model organism in diabetes research. Its glucose metabolism and the pathways of reactive metabolite formation are very similar to those of humans. Moreover, several physiological and pathophysiological pathways that also exist in humans and other mammals have been identified in this species or are currently under intense investigation. Zebrafish offer sophisticated imaging techniques and allow simple and fast genetic and pharmacological approaches with a high throughput. In this review, we highlight achievements and mechanisms concerning microvascular complications discovered in zebrafish, and we discuss the advantages and disadvantages of zebrafish as a model for studying diabetic complications.

Aggregate and Individual Replication Probability within an Explicit Model of the Research Process

Science.gov (United States)

Miller, Jeff; Schwarz, Wolf

2011-01-01

We study a model of the research process in which the true effect size, the replication jitter due to changes in experimental procedure, and the statistical error of effect size measurement are all normally distributed random variables. Within this model, we analyze the probability of successfully replicating an initial experimental result by…

Methods for Reducing Normal Tissue Complication Probabilities in Oropharyngeal Cancer: Dose Reduction or Planning Target Volume Elimination

Energy Technology Data Exchange (ETDEWEB)

Samuels, Stuart E.; Eisbruch, Avraham; Vineberg, Karen; Lee, Jae; Lee, Choonik; Matuszak, Martha M.; Ten Haken, Randall K.; Brock, Kristy K., E-mail: kbrock@med.umich.edu

2016-11-01

Purpose: Strategies to reduce the toxicities of head and neck radiation (ie, dysphagia [difficulty swallowing] and xerostomia [dry mouth]) are currently underway. However, the predicted benefit of dose and planning target volume (PTV) reduction strategies is unknown. The purpose of the present study was to compare the normal tissue complication probabilities (NTCP) for swallowing and salivary structures in standard plans (70 Gy [P70]), dose-reduced plans (60 Gy [P60]), and plans eliminating the PTV margin. Methods and Materials: A total of 38 oropharyngeal cancer (OPC) plans were analyzed. Standard organ-sparing volumetric modulated arc therapy plans (P70) were created and then modified by eliminating the PTVs and treating the clinical tumor volumes (CTVs) only (C70) or maintaining the PTV but reducing the dose to 60 Gy (P60). NTCP dose models for the pharyngeal constrictors, glottis/supraglottic larynx, parotid glands (PGs), and submandibular glands (SMGs) were analyzed. The minimal clinically important benefit was defined as a mean change in NTCP of >5%. The P70 NTCP thresholds and overlap percentages of the organs at risk with the PTVs (56-59 Gy, vPTV{sub 56}) were evaluated to identify the predictors for NTCP improvement. Results: With the P60 plans, only the ipsilateral PG (iPG) benefited (23.9% vs 16.2%; P<.01). With the C70 plans, only the iPG (23.9% vs 17.5%; P<.01) and contralateral SMG (cSMG) (NTCP 32.1% vs 22.9%; P<.01) benefited. An iPG NTCP threshold of 20% and 30% predicted NTCP benefits for the P60 and C70 plans, respectively (P<.001). A cSMG NTCP threshold of 30% predicted for an NTCP benefit with the C70 plans (P<.001). Furthermore, for the iPG, a vPTV{sub 56} >13% predicted benefit with P60 (P<.001) and C70 (P=.002). For the cSMG, a vPTV{sub 56} >22% predicted benefit with C70 (P<.01). Conclusions: PTV elimination and dose-reduction lowered the NTCP of the iPG, and PTV elimination lowered the NTCP of the cSMG. NTCP thresholds and the

Sampling the stream landscape: Improving the applicability of an ecoregion-level capture probability model for stream fishes

Science.gov (United States)

Mollenhauer, Robert; Mouser, Joshua B.; Brewer, Shannon K.

2018-01-01

Temporal and spatial variability in streams result in heterogeneous gear capture probability (i.e., the proportion of available individuals identified) that confounds interpretation of data used to monitor fish abundance. We modeled tow-barge electrofishing capture probability at multiple spatial scales for nine Ozark Highland stream fishes. In addition to fish size, we identified seven reach-scale environmental characteristics associated with variable capture probability: stream discharge, water depth, conductivity, water clarity, emergent vegetation, wetted width–depth ratio, and proportion of riffle habitat. The magnitude of the relationship between capture probability and both discharge and depth varied among stream fishes. We also identified lithological characteristics among stream segments as a coarse-scale source of variable capture probability. The resulting capture probability model can be used to adjust catch data and derive reach-scale absolute abundance estimates across a wide range of sampling conditions with similar effort as used in more traditional fisheries surveys (i.e., catch per unit effort). Adjusting catch data based on variable capture probability improves the comparability of data sets, thus promoting both well-informed conservation and management decisions and advances in stream-fish ecology.

Modeling co-occurrence of northern spotted and barred owls: accounting for detection probability differences

Science.gov (United States)

Bailey, Larissa L.; Reid, Janice A.; Forsman, Eric D.; Nichols, James D.

2009-01-01

Barred owls (Strix varia) have recently expanded their range and now encompass the entire range of the northern spotted owl (Strix occidentalis caurina). This expansion has led to two important issues of concern for management of northern spotted owls: (1) possible competitive interactions between the two species that could contribute to population declines of northern spotted owls, and (2) possible changes in vocalization behavior and detection probabilities of northern spotted owls induced by presence of barred owls. We used a two-species occupancy model to investigate whether there was evidence of competitive exclusion between the two species at study locations in Oregon, USA. We simultaneously estimated detection probabilities for both species and determined if the presence of one species influenced the detection of the other species. Model selection results and associated parameter estimates provided no evidence that barred owls excluded spotted owls from territories. We found strong evidence that detection probabilities differed for the two species, with higher probabilities for northern spotted owls that are the object of current surveys. Non-detection of barred owls is very common in surveys for northern spotted owls, and detection of both owl species was negatively influenced by the presence of the congeneric species. Our results suggest that analyses directed at hypotheses of barred owl effects on demographic or occupancy vital rates of northern spotted owls need to deal adequately with imperfect and variable detection probabilities for both species.

The role of high fat diet in the development of complications of chronic pancreatitis.

Science.gov (United States)

Castiñeira-Alvariño, M; Lindkvist, B; Luaces-Regueira, M; Iglesias-García, J; Lariño-Noia, J; Nieto-García, L; Domínguez-Muñoz, J E

2013-10-01

Little is known about risk factors for complications in chronic pancreatitis (CP). High fat diet (HFD) has been demonstrated to aggravate pancreatic injury in animal models. The aim of this study was to investigate the role of HFD in age at diagnosis of CP and probability of CP related complications. A cross-sectional case-case study was performed within a prospectively collected cohort of patients with CP. Diagnosis and morphological severity of CP was established by endoscopic ultrasound. Pancreatic exocrine insufficiency (PEI) was diagnosed by ¹³C mixed triglyceride breath test. Fat intake was assessed by a specific nutritional questionnaire. Odds ratios (OR) for CP related complications were estimated by multivariate logistic regression analysis. 168 patients were included (128 (76.2%) men, mean age 44 years (SD 13.5)). Etiology of CP was alcohol abuse in 89 patients (53.0%), other causes in 30 (17.9%) and idiopathic in the remaining 49 subjects (29.2%). 24 patients (14.3%) had a HFD. 68 patients (40.5%) had continuous abdominal pain, 39 (23.2%) PEI and 43 (25.7%) morphologically severe CP. HFD was associated with an increased probability for continuous abdominal pain (OR = 2.84 (95% CI, 1.06-7.61)), and a younger age at diagnosis (37.0 ± 13.9 versus 45.8 ± 13.0 years, p = 0.03) but not with CP related complications after adjusting for sex, years of follow-up, alcohol and tobacco consumption, etiology and body mass index. Compared with a normal fat diet, HFD is associated with a younger age at diagnosis of CP and continuous abdominal pain, but not with severity and complications of the disease. Copyright © 2013 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Probability-based collaborative filtering model for predicting gene-disease associations.

Science.gov (United States)

Zeng, Xiangxiang; Ding, Ningxiang; Rodríguez-Patón, Alfonso; Zou, Quan

2017-12-28

Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene-disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our model. Firstly, on the basis of a typical latent factorization model, we propose model I with an average heterogeneous regularization. Secondly, we develop modified model II with personal heterogeneous regularization to enhance the accuracy of aforementioned models. In this model, vector space similarity or Pearson correlation coefficient metrics and data on related species are also used. We compared the results of PCFM with the results of four state-of-arts approaches. The results show that PCFM performs better than other advanced approaches. PCFM model can be leveraged for predictions of disease genes, especially for new human genes or diseases with no known relationships.

Introduction to probability with R

CERN Document Server

Baclawski, Kenneth

2008-01-01

FOREWORD PREFACE Sets, Events, and Probability The Algebra of Sets The Bernoulli Sample Space The Algebra of Multisets The Concept of Probability Properties of Probability Measures Independent Events The Bernoulli Process The R Language Finite Processes The Basic Models Counting Rules Computing Factorials The Second Rule of Counting Computing Probabilities Discrete Random Variables The Bernoulli Process: Tossing a Coin The Bernoulli Process: Random Walk Independence and Joint Distributions Expectations The Inclusion-Exclusion Principle General Random Variable

External validation of a normal tissue complication probability model for radiation-induced hypothyroidism in an independent cohort

DEFF Research Database (Denmark)

Rønjom, Marianne F; Brink, Carsten; Bentzen, Søren M

2015-01-01

blood tests in the validation cohort relative to the original cohort. However, Pearson's correlation coefficients between model and clinical outcome were high: r = 0.97 estimated by the original model versus the original cohort, and r = 0.97 estimated by the original model versus the new cohort....... CONCLUSION: Dmean and Vthyroid were significant predictors of RIHT in both cohorts. The original NTCP model demonstrated external validity owing to high Pearson's correlation coefficients between estimated and observed incidence rates of RIHT in the original as well as in the validation cohort. This model...

Assessing the clinical probability of pulmonary embolism

International Nuclear Information System (INIS)

Miniati, M.; Pistolesi, M.

2001-01-01

Clinical assessment is a cornerstone of the recently validated diagnostic strategies for pulmonary embolism (PE). Although the diagnostic yield of individual symptoms, signs, and common laboratory tests is limited, the combination of these variables, either by empirical assessment or by a prediction rule, can be used to express a clinical probability of PE. The latter may serve as pretest probability to predict the probability of PE after further objective testing (posterior or post-test probability). Over the last few years, attempts have been made to develop structured prediction models for PE. In a Canadian multicenter prospective study, the clinical probability of PE was rated as low, intermediate, or high according to a model which included assessment of presenting symptoms and signs, risk factors, and presence or absence of an alternative diagnosis at least as likely as PE. Recently, a simple clinical score was developed to stratify outpatients with suspected PE into groups with low, intermediate, or high clinical probability. Logistic regression was used to predict parameters associated with PE. A score ≤ 4 identified patients with low probability of whom 10% had PE. The prevalence of PE in patients with intermediate (score 5-8) and high probability (score ≥ 9) was 38 and 81%, respectively. As opposed to the Canadian model, this clinical score is standardized. The predictor variables identified in the model, however, were derived from a database of emergency ward patients. This model may, therefore, not be valid in assessing the clinical probability of PE in inpatients. In the PISA-PED study, a clinical diagnostic algorithm was developed which rests on the identification of three relevant clinical symptoms and on their association with electrocardiographic and/or radiographic abnormalities specific for PE. Among patients who, according to the model, had been rated as having a high clinical probability, the prevalence of proven PE was 97%, while it was 3

Truth, possibility and probability new logical foundations of probability and statistical inference

CERN Document Server

Chuaqui, R

1991-01-01

Anyone involved in the philosophy of science is naturally drawn into the study of the foundations of probability. Different interpretations of probability, based on competing philosophical ideas, lead to different statistical techniques, and frequently to mutually contradictory consequences. This unique book presents a new interpretation of probability, rooted in the traditional interpretation that was current in the 17th and 18th centuries. Mathematical models are constructed based on this interpretation, and statistical inference and decision theory are applied, including some examples in artificial intelligence, solving the main foundational problems. Nonstandard analysis is extensively developed for the construction of the models and in some of the proofs. Many nonstandard theorems are proved, some of them new, in particular, a representation theorem that asserts that any stochastic process can be approximated by a process defined over a space with equiprobable outcomes.

Probability of atrial fibrillation after ablation: Using a parametric nonlinear temporal decomposition mixed effects model.

Science.gov (United States)

Rajeswaran, Jeevanantham; Blackstone, Eugene H; Ehrlinger, John; Li, Liang; Ishwaran, Hemant; Parides, Michael K

2018-01-01

Atrial fibrillation is an arrhythmic disorder where the electrical signals of the heart become irregular. The probability of atrial fibrillation (binary response) is often time varying in a structured fashion, as is the influence of associated risk factors. A generalized nonlinear mixed effects model is presented to estimate the time-related probability of atrial fibrillation using a temporal decomposition approach to reveal the pattern of the probability of atrial fibrillation and their determinants. This methodology generalizes to patient-specific analysis of longitudinal binary data with possibly time-varying effects of covariates and with different patient-specific random effects influencing different temporal phases. The motivation and application of this model is illustrated using longitudinally measured atrial fibrillation data obtained through weekly trans-telephonic monitoring from an NIH sponsored clinical trial being conducted by the Cardiothoracic Surgery Clinical Trials Network.

Establishing Differences in Thermographic Patterns between the Various Complications in Diabetic Foot Disease

Directory of Open Access Journals (Sweden)

Alfred Gatt

2018-01-01

Full Text Available Aim. To evaluate the potential of thermography as an assessment tool for the detection of foot complications by understanding the variations in temperature that occur in type 2 diabetes mellitus (DM. Methods. Participants were categorized according to a medical examination, ankle brachial index, doppler waveform analysis, and 10-gram monofilament testing into five groups: healthy adult, DM with no complications, DM with peripheral neuropathy, DM with neuroischaemia, and DM with peripheral arterial disease (PAD groups. Thermographic imaging of the toes and forefeet was performed. Results. 43 neuroischaemic feet, 41 neuropathic feet, 58 PAD feet, 21 DM feet without complications, and 126 healthy feet were analyzed. The temperatures of the feet and toes were significantly higher in the complications group when compared to the healthy adult and DM healthy groups. The higher the temperatures of the foot in DM, the higher the probability that it is affected by neuropathy, neuroischaemia, or PAD. Conclusions. Significant differences in mean temperatures exist between participants who were healthy and those with DM with no known complications when compared to participants with neuroischaemia, neuropathy, or PAD. As foot temperature rises, so does the probability of the presence of complications of neuropathy, neuroischaemia, or peripheral arterial disease.

Properties of the probability distribution associated with the largest event in an earthquake cluster and their implications to foreshocks

International Nuclear Information System (INIS)

Zhuang Jiancang; Ogata, Yosihiko

2006-01-01

The space-time epidemic-type aftershock sequence model is a stochastic branching process in which earthquake activity is classified into background and clustering components and each earthquake triggers other earthquakes independently according to certain rules. This paper gives the probability distributions associated with the largest event in a cluster and their properties for all three cases when the process is subcritical, critical, and supercritical. One of the direct uses of these probability distributions is to evaluate the probability of an earthquake to be a foreshock, and magnitude distributions of foreshocks and nonforeshock earthquakes. To verify these theoretical results, the Japan Meteorological Agency earthquake catalog is analyzed. The proportion of events that have 1 or more larger descendants in total events is found to be as high as about 15%. When the differences between background events and triggered event in the behavior of triggering children are considered, a background event has a probability about 8% to be a foreshock. This probability decreases when the magnitude of the background event increases. These results, obtained from a complicated clustering model, where the characteristics of background events and triggered events are different, are consistent with the results obtained in [Ogata et al., Geophys. J. Int. 127, 17 (1996)] by using the conventional single-linked cluster declustering method

Properties of the probability distribution associated with the largest event in an earthquake cluster and their implications to foreshocks.

Science.gov (United States)

Zhuang, Jiancang; Ogata, Yosihiko

2006-04-01

The space-time epidemic-type aftershock sequence model is a stochastic branching process in which earthquake activity is classified into background and clustering components and each earthquake triggers other earthquakes independently according to certain rules. This paper gives the probability distributions associated with the largest event in a cluster and their properties for all three cases when the process is subcritical, critical, and supercritical. One of the direct uses of these probability distributions is to evaluate the probability of an earthquake to be a foreshock, and magnitude distributions of foreshocks and nonforeshock earthquakes. To verify these theoretical results, the Japan Meteorological Agency earthquake catalog is analyzed. The proportion of events that have 1 or more larger descendants in total events is found to be as high as about 15%. When the differences between background events and triggered event in the behavior of triggering children are considered, a background event has a probability about 8% to be a foreshock. This probability decreases when the magnitude of the background event increases. These results, obtained from a complicated clustering model, where the characteristics of background events and triggered events are different, are consistent with the results obtained in [Ogata, Geophys. J. Int. 127, 17 (1996)] by using the conventional single-linked cluster declustering method.

The ruin probability of a discrete time risk model under constant interest rate with heavy tails

NARCIS (Netherlands)

Tang, Q.

2004-01-01

This paper investigates the ultimate ruin probability of a discrete time risk model with a positive constant interest rate. Under the assumption that the gross loss of the company within one year is subexponentially distributed, a simple asymptotic relation for the ruin probability is derived and

Three-dimensional analytic probabilities of coupled vibrational-rotational-translational energy transfer for DSMC modeling of nonequilibrium flows

International Nuclear Information System (INIS)

Adamovich, Igor V.

2014-01-01

A three-dimensional, nonperturbative, semiclassical analytic model of vibrational energy transfer in collisions between a rotating diatomic molecule and an atom, and between two rotating diatomic molecules (Forced Harmonic Oscillator–Free Rotation model) has been extended to incorporate rotational relaxation and coupling between vibrational, translational, and rotational energy transfer. The model is based on analysis of semiclassical trajectories of rotating molecules interacting by a repulsive exponential atom-to-atom potential. The model predictions are compared with the results of three-dimensional close-coupled semiclassical trajectory calculations using the same potential energy surface. The comparison demonstrates good agreement between analytic and numerical probabilities of rotational and vibrational energy transfer processes, over a wide range of total collision energies, rotational energies, and impact parameter. The model predicts probabilities of single-quantum and multi-quantum vibrational-rotational transitions and is applicable up to very high collision energies and quantum numbers. Closed-form analytic expressions for these transition probabilities lend themselves to straightforward incorporation into DSMC nonequilibrium flow codes

Probability Theory Plus Noise: Descriptive Estimation and Inferential Judgment.

Science.gov (United States)

Costello, Fintan; Watts, Paul

2018-01-01

We describe a computational model of two central aspects of people's probabilistic reasoning: descriptive probability estimation and inferential probability judgment. This model assumes that people's reasoning follows standard frequentist probability theory, but it is subject to random noise. This random noise has a regressive effect in descriptive probability estimation, moving probability estimates away from normative probabilities and toward the center of the probability scale. This random noise has an anti-regressive effect in inferential judgement, however. These regressive and anti-regressive effects explain various reliable and systematic biases seen in people's descriptive probability estimation and inferential probability judgment. This model predicts that these contrary effects will tend to cancel out in tasks that involve both descriptive estimation and inferential judgement, leading to unbiased responses in those tasks. We test this model by applying it to one such task, described by Gallistel et al. ). Participants' median responses in this task were unbiased, agreeing with normative probability theory over the full range of responses. Our model captures the pattern of unbiased responses in this task, while simultaneously explaining systematic biases away from normatively correct probabilities seen in other tasks. Copyright © 2018 Cognitive Science Society, Inc.

The return period analysis of natural disasters with statistical modeling of bivariate joint probability distribution.

Science.gov (United States)

Li, Ning; Liu, Xueqin; Xie, Wei; Wu, Jidong; Zhang, Peng

2013-01-01

New features of natural disasters have been observed over the last several years. The factors that influence the disasters' formation mechanisms, regularity of occurrence and main characteristics have been revealed to be more complicated and diverse in nature than previously thought. As the uncertainty involved increases, the variables need to be examined further. This article discusses the importance and the shortage of multivariate analysis of natural disasters and presents a method to estimate the joint probability of the return periods and perform a risk analysis. Severe dust storms from 1990 to 2008 in Inner Mongolia were used as a case study to test this new methodology, as they are normal and recurring climatic phenomena on Earth. Based on the 79 investigated events and according to the dust storm definition with bivariate, the joint probability distribution of severe dust storms was established using the observed data of maximum wind speed and duration. The joint return periods of severe dust storms were calculated, and the relevant risk was analyzed according to the joint probability. The copula function is able to simulate severe dust storm disasters accurately. The joint return periods generated are closer to those observed in reality than the univariate return periods and thus have more value in severe dust storm disaster mitigation, strategy making, program design, and improvement of risk management. This research may prove useful in risk-based decision making. The exploration of multivariate analysis methods can also lay the foundation for further applications in natural disaster risk analysis. © 2012 Society for Risk Analysis.

Risk estimation using probability machines

Science.gov (United States)

2014-01-01

Background Logistic regression has been the de facto, and often the only, model used in the description and analysis of relationships between a binary outcome and observed features. It is widely used to obtain the conditional probabilities of the outcome given predictors, as well as predictor effect size estimates using conditional odds ratios. Results We show how statistical learning machines for binary outcomes, provably consistent for the nonparametric regression problem, can be used to provide both consistent conditional probability estimation and conditional effect size estimates. Effect size estimates from learning machines leverage our understanding of counterfactual arguments central to the interpretation of such estimates. We show that, if the data generating model is logistic, we can recover accurate probability predictions and effect size estimates with nearly the same efficiency as a correct logistic model, both for main effects and interactions. We also propose a method using learning machines to scan for possible interaction effects quickly and efficiently. Simulations using random forest probability machines are presented. Conclusions The models we propose make no assumptions about the data structure, and capture the patterns in the data by just specifying the predictors involved and not any particular model structure. So they do not run the same risks of model mis-specification and the resultant estimation biases as a logistic model. This methodology, which we call a “risk machine”, will share properties from the statistical machine that it is derived from. PMID:24581306

Alternative probability theories for cognitive psychology.

Science.gov (United States)

Narens, Louis

2014-01-01

Various proposals for generalizing event spaces for probability functions have been put forth in the mathematical, scientific, and philosophic literatures. In cognitive psychology such generalizations are used for explaining puzzling results in decision theory and for modeling the influence of context effects. This commentary discusses proposals for generalizing probability theory to event spaces that are not necessarily boolean algebras. Two prominent examples are quantum probability theory, which is based on the set of closed subspaces of a Hilbert space, and topological probability theory, which is based on the set of open sets of a topology. Both have been applied to a variety of cognitive situations. This commentary focuses on how event space properties can influence probability concepts and impact cognitive modeling. Copyright © 2013 Cognitive Science Society, Inc.

Transition probability spaces in loop quantum gravity

Science.gov (United States)

Guo, Xiao-Kan

2018-03-01

We study the (generalized) transition probability spaces, in the sense of Mielnik and Cantoni, for spacetime quantum states in loop quantum gravity. First, we show that loop quantum gravity admits the structures of transition probability spaces. This is exemplified by first checking such structures in covariant quantum mechanics and then identifying the transition probability spaces in spin foam models via a simplified version of general boundary formulation. The transition probability space thus defined gives a simple way to reconstruct the discrete analog of the Hilbert space of the canonical theory and the relevant quantum logical structures. Second, we show that the transition probability space and in particular the spin foam model are 2-categories. Then we discuss how to realize in spin foam models two proposals by Crane about the mathematical structures of quantum gravity, namely, the quantum topos and causal sites. We conclude that transition probability spaces provide us with an alternative framework to understand various foundational questions of loop quantum gravity.

Complications from arteriovenous malformation radiosurgery: multivariate analysis and risk modeling

International Nuclear Information System (INIS)

Flickinger, John C.; Kondziolka, Douglas; Pollock, Bruce E.; Maitz, Ann H.; Lunsford, L. Dade

1997-01-01

Purpose/Objective: To assess the relationships of radiosurgery treatment parameters to the development of complications from radiosurgery for arteriovenous malformations (AVM). Methods and Materials: We evaluated follow-up imaging and clinical data in 307 AVM patients who received gamma knife radiosurgery at the University of Pittsburgh between 1987 and 1993. All patients had regular clinical or imaging follow up for a minimum of 2 years (range: 24-96 months, median = 44 months). Results: Post-radiosurgical imaging (PRI) changes developed in 30.5% of patients with regular follow-up magnetic resonance imaging, and were symptomatic in 10.7% of all patients at 7 years. PRI changes resolved within 3 years developed significantly less often (p = 0.0274) in patients with symptoms (52.8%) compared to asymptomatic patients (94.8%). The 7-year actuarial rate for developing persistent symptomatic PRI changes was 5.05%. Multivariate logistic regression modeling found that the 12 Gy volume was the only independent variable that correlated significantly with PRI changes (p < 0.0001) while symptomatic PRI changes were correlated with both 12 Gy volume (p = 0.0013) and AVM location (p 0.0066). Conclusion: Complications from AVM radiosurgery can be predicted with a statistical model relating the risks of developing symptomatic post-radiosurgical imaging changes to 12 Gy treatment volume and location

OL-DEC-MDP Model for Multiagent Online Scheduling with a Time-Dependent Probability of Success

Directory of Open Access Journals (Sweden)

Cheng Zhu

2014-01-01

Full Text Available Focusing on the on-line multiagent scheduling problem, this paper considers the time-dependent probability of success and processing duration and proposes an OL-DEC-MDP (opportunity loss-decentralized Markov Decision Processes model to include opportunity loss into scheduling decision to improve overall performance. The success probability of job processing as well as the process duration is dependent on the time at which the processing is started. The probability of completing the assigned job by an agent would be higher when the process is started earlier, but the opportunity loss could also be high due to the longer engaging duration. As a result, OL-DEC-MDP model introduces a reward function considering the opportunity loss, which is estimated based on the prediction of the upcoming jobs by a sampling method on the job arrival. Heuristic strategies are introduced in computing the best starting time for an incoming job by each agent, and an incoming job will always be scheduled to the agent with the highest reward among all agents with their best starting policies. The simulation experiments show that the OL-DEC-MDP model will improve the overall scheduling performance compared with models not considering opportunity loss in heavy-loading environment.

On complicity theory.

Science.gov (United States)

Kline, A David

2006-04-01

The received account of whistleblowing, developed over the last quarter century, is identified with the work of Norman Bowie and Richard DeGeorge. Michael Davis has detailed three anomalies for the received view: the paradoxes of burden, missing harm and failure. In addition, he has proposed an alternative account of whistleblowing, viz., the Complicity Theory. This paper examines the Complicity Theory. The supposed anomalies rest on misunderstandings of the received view or misreadings of model cases of whistleblowing, for example, the Challenger disaster and the Ford Pinto. Nevertheless, the Complicity Theory is important for as in science the contrast with alternative competing accounts often helps us better understand the received view. Several aspects of the received view are reviewed and strengthened through comparison with Complicity Theory, including why whistleblowing needs moral justification. Complicity Theory is also critiqued. The fundamental failure of Complicity Theory is its failure to explain why government and the public encourage and protect whistleblowers despite the possibility of considerable harm to the relevant company in reputation, lost jobs, and lost shareholder value.

Interpreting and Understanding Logits, Probits, and other Non-Linear Probability Models

DEFF Research Database (Denmark)

Breen, Richard; Karlson, Kristian Bernt; Holm, Anders

2018-01-01

Methods textbooks in sociology and other social sciences routinely recommend the use of the logit or probit model when an outcome variable is binary, an ordered logit or ordered probit when it is ordinal, and a multinomial logit when it has more than two categories. But these methodological...... guidelines take little or no account of a body of work that, over the past 30 years, has pointed to problematic aspects of these nonlinear probability models and, particularly, to difficulties in interpreting their parameters. In this chapterreview, we draw on that literature to explain the problems, show...

Estimating Subjective Probabilities

DEFF Research Database (Denmark)

Andersen, Steffen; Fountain, John; Harrison, Glenn W.

2014-01-01

either construct elicitation mechanisms that control for risk aversion, or construct elicitation mechanisms which undertake 'calibrating adjustments' to elicited reports. We illustrate how the joint estimation of risk attitudes and subjective probabilities can provide the calibration adjustments...... that theory calls for. We illustrate this approach using data from a controlled experiment with real monetary consequences to the subjects. This allows the observer to make inferences about the latent subjective probability, under virtually any well-specified model of choice under subjective risk, while still...

Predicting Cumulative Incidence Probability by Direct Binomial Regression

DEFF Research Database (Denmark)

Scheike, Thomas H.; Zhang, Mei-Jie

Binomial modelling; cumulative incidence probability; cause-specific hazards; subdistribution hazard......Binomial modelling; cumulative incidence probability; cause-specific hazards; subdistribution hazard...

Blind Students' Learning of Probability through the Use of a Tactile Model

Science.gov (United States)

Vita, Aida Carvalho; Kataoka, Verônica Yumi

2014-01-01

The objective of this paper is to discuss how blind students learn basic concepts of probability using the tactile model proposed by Vita (2012). Among the activities were part of the teaching sequence "Jefferson's Random Walk", in which students built a tree diagram (using plastic trays, foam cards, and toys), and pictograms in 3D…

Probability Distributome: A Web Computational Infrastructure for Exploring the Properties, Interrelations, and Applications of Probability Distributions.

Science.gov (United States)

Dinov, Ivo D; Siegrist, Kyle; Pearl, Dennis K; Kalinin, Alexandr; Christou, Nicolas

2016-06-01

Probability distributions are useful for modeling, simulation, analysis, and inference on varieties of natural processes and physical phenomena. There are uncountably many probability distributions. However, a few dozen families of distributions are commonly defined and are frequently used in practice for problem solving, experimental applications, and theoretical studies. In this paper, we present a new computational and graphical infrastructure, the Distributome , which facilitates the discovery, exploration and application of diverse spectra of probability distributions. The extensible Distributome infrastructure provides interfaces for (human and machine) traversal, search, and navigation of all common probability distributions. It also enables distribution modeling, applications, investigation of inter-distribution relations, as well as their analytical representations and computational utilization. The entire Distributome framework is designed and implemented as an open-source, community-built, and Internet-accessible infrastructure. It is portable, extensible and compatible with HTML5 and Web2.0 standards (http://Distributome.org). We demonstrate two types of applications of the probability Distributome resources: computational research and science education. The Distributome tools may be employed to address five complementary computational modeling applications (simulation, data-analysis and inference, model-fitting, examination of the analytical, mathematical and computational properties of specific probability distributions, and exploration of the inter-distributional relations). Many high school and college science, technology, engineering and mathematics (STEM) courses may be enriched by the use of modern pedagogical approaches and technology-enhanced methods. The Distributome resources provide enhancements for blended STEM education by improving student motivation, augmenting the classical curriculum with interactive webapps, and overhauling the

[Biometric bases: basic concepts of probability calculation].

Science.gov (United States)

Dinya, E

1998-04-26

The author gives or outline of the basic concepts of probability theory. The bases of the event algebra, definition of the probability, the classical probability model and the random variable are presented.

Path Loss, Shadow Fading, and Line-Of-Sight Probability Models for 5G Urban Macro-Cellular Scenarios

DEFF Research Database (Denmark)

Sun, Shu; Thomas, Timothy; Rappaport, Theodore S.

2015-01-01

This paper presents key parameters including the line-of-sight (LOS) probability, large-scale path loss, and shadow fading models for the design of future fifth generation (5G) wireless communication systems in urban macro-cellular (UMa) scenarios, using the data obtained from propagation...... measurements in Austin, US, and Aalborg, Denmark, at 2, 10, 18, and 38 GHz. A comparison of different LOS probability models is performed for the Aalborg environment. Both single-slope and dual-slope omnidirectional path loss models are investigated to analyze and contrast their root-mean-square (RMS) errors...

Predicting binary choices from probability phrase meanings.

Science.gov (United States)

Wallsten, Thomas S; Jang, Yoonhee

2008-08-01

The issues of how individuals decide which of two events is more likely and of how they understand probability phrases both involve judging relative likelihoods. In this study, we investigated whether derived scales representing probability phrase meanings could be used within a choice model to predict independently observed binary choices. If they can, this simultaneously provides support for our model and suggests that the phrase meanings are measured meaningfully. The model assumes that, when deciding which of two events is more likely, judges take a single sample from memory regarding each event and respond accordingly. The model predicts choice probabilities by using the scaled meanings of individually selected probability phrases as proxies for confidence distributions associated with sampling from memory. Predictions are sustained for 34 of 41 participants but, nevertheless, are biased slightly low. Sequential sampling models improve the fit. The results have both theoretical and applied implications.

Modeling Stress Strain Relationships and Predicting Failure Probabilities For Graphite Core Components

Energy Technology Data Exchange (ETDEWEB)

Duffy, Stephen [Cleveland State Univ., Cleveland, OH (United States)

2013-09-09

This project will implement inelastic constitutive models that will yield the requisite stress-strain information necessary for graphite component design. Accurate knowledge of stress states (both elastic and inelastic) is required to assess how close a nuclear core component is to failure. Strain states are needed to assess deformations in order to ascertain serviceability issues relating to failure, e.g., whether too much shrinkage has taken place for the core to function properly. Failure probabilities, as opposed to safety factors, are required in order to capture the bariability in failure strength in tensile regimes. The current stress state is used to predict the probability of failure. Stochastic failure models will be developed that can accommodate possible material anisotropy. This work will also model material damage (i.e., degradation of mechanical properties) due to radiation exposure. The team will design tools for components fabricated from nuclear graphite. These tools must readily interact with finite element software--in particular, COMSOL, the software algorithm currently being utilized by the Idaho National Laboratory. For the eleastic response of graphite, the team will adopt anisotropic stress-strain relationships available in COMSO. Data from the literature will be utilized to characterize the appropriate elastic material constants.

Modeling Stress Strain Relationships and Predicting Failure Probabilities For Graphite Core Components

International Nuclear Information System (INIS)

Duffy, Stephen

2013-01-01

This project will implement inelastic constitutive models that will yield the requisite stress-strain information necessary for graphite component design. Accurate knowledge of stress states (both elastic and inelastic) is required to assess how close a nuclear core component is to failure. Strain states are needed to assess deformations in order to ascertain serviceability issues relating to failure, e.g., whether too much shrinkage has taken place for the core to function properly. Failure probabilities, as opposed to safety factors, are required in order to capture the bariability in failure strength in tensile regimes. The current stress state is used to predict the probability of failure. Stochastic failure models will be developed that can accommodate possible material anisotropy. This work will also model material damage (i.e., degradation of mechanical properties) due to radiation exposure. The team will design tools for components fabricated from nuclear graphite. These tools must readily interact with finite element software--in particular, COMSOL, the software algorithm currently being utilized by the Idaho National Laboratory. For the eleastic response of graphite, the team will adopt anisotropic stress-strain relationships available in COMSO. Data from the literature will be utilized to characterize the appropriate elastic material constants.

A transmission/escape probabilities model for neutral particle transport in the outer regions of a diverted tokamak

International Nuclear Information System (INIS)

Stacey, W.M.

1992-12-01

A new computational model for neutral particle transport in the outer regions of a diverted tokamak plasma chamber is presented. The model is based on the calculation of transmission and escape probabilities using first-flight integral transport theory and the balancing of fluxes across the surfaces bounding the various regions. The geometrical complexity of the problem is included in precomputed probabilities which depend only on the mean free path of the region

Expected utility with lower probabilities

DEFF Research Database (Denmark)

Hendon, Ebbe; Jacobsen, Hans Jørgen; Sloth, Birgitte

1994-01-01

An uncertain and not just risky situation may be modeled using so-called belief functions assigning lower probabilities to subsets of outcomes. In this article we extend the von Neumann-Morgenstern expected utility theory from probability measures to belief functions. We use this theory...

High-resolution urban flood modelling - a joint probability approach

Science.gov (United States)

Hartnett, Michael; Olbert, Agnieszka; Nash, Stephen

2017-04-01

(Divoky et al., 2005). Nevertheless, such events occur and in Ireland alone there are several cases of serious damage due to flooding resulting from a combination of high sea water levels and river flows driven by the same meteorological conditions (e.g. Olbert et al. 2015). A November 2009 fluvial-coastal flooding of Cork City bringing €100m loss was one such incident. This event was used by Olbert et al. (2015) to determine processes controlling urban flooding and is further explored in this study to elaborate on coastal and fluvial flood mechanisms and their roles in controlling water levels. The objective of this research is to develop a methodology to assess combined effect of multiple source flooding on flood probability and severity in urban areas and to establish a set of conditions that dictate urban flooding due to extreme climatic events. These conditions broadly combine physical flood drivers (such as coastal and fluvial processes), their mechanisms and thresholds defining flood severity. The two main physical processes controlling urban flooding: high sea water levels (coastal flooding) and high river flows (fluvial flooding), and their threshold values for which flood is likely to occur, are considered in this study. Contribution of coastal and fluvial drivers to flooding and their impacts are assessed in a two-step process. The first step involves frequency analysis and extreme value statistical modelling of storm surges, tides and river flows and ultimately the application of joint probability method to estimate joint exceedence return periods for combination of surges, tide and river flows. In the second step, a numerical model of Cork Harbour MSN_Flood comprising a cascade of four nested high-resolution models is used to perform simulation of flood inundation under numerous hypothetical coastal and fluvial flood scenarios. The risk of flooding is quantified based on a range of physical aspects such as the extent and depth of inundation (Apel et al

Time series modeling of pathogen-specific disease probabilities with subsampled data.

Science.gov (United States)

Fisher, Leigh; Wakefield, Jon; Bauer, Cici; Self, Steve

2017-03-01

Many diseases arise due to exposure to one of multiple possible pathogens. We consider the situation in which disease counts are available over time from a study region, along with a measure of clinical disease severity, for example, mild or severe. In addition, we suppose a subset of the cases are lab tested in order to determine the pathogen responsible for disease. In such a context, we focus interest on modeling the probabilities of disease incidence given pathogen type. The time course of these probabilities is of great interest as is the association with time-varying covariates such as meteorological variables. In this set up, a natural Bayesian approach would be based on imputation of the unsampled pathogen information using Markov Chain Monte Carlo but this is computationally challenging. We describe a practical approach to inference that is easy to implement. We use an empirical Bayes procedure in a first step to estimate summary statistics. We then treat these summary statistics as the observed data and develop a Bayesian generalized additive model. We analyze data on hand, foot, and mouth disease (HFMD) in China in which there are two pathogens of primary interest, enterovirus 71 (EV71) and Coxackie A16 (CA16). We find that both EV71 and CA16 are associated with temperature, relative humidity, and wind speed, with reasonably similar functional forms for both pathogens. The important issue of confounding by time is modeled using a penalized B-spline model with a random effects representation. The level of smoothing is addressed by a careful choice of the prior on the tuning variance. © 2016, The International Biometric Society.

Various models for pion probability distributions from heavy-ion collisions

International Nuclear Information System (INIS)

Mekjian, A.Z.; Mekjian, A.Z.; Schlei, B.R.; Strottman, D.; Schlei, B.R.

1998-01-01

Various models for pion multiplicity distributions produced in relativistic heavy ion collisions are discussed. The models include a relativistic hydrodynamic model, a thermodynamic description, an emitting source pion laser model, and a description which generates a negative binomial description. The approach developed can be used to discuss other cases which will be mentioned. The pion probability distributions for these various cases are compared. Comparison of the pion laser model and Bose-Einstein condensation in a laser trap and with the thermal model are made. The thermal model and hydrodynamic model are also used to illustrate why the number of pions never diverges and why the Bose-Einstein correction effects are relatively small. The pion emission strength η of a Poisson emitter and a critical density η c are connected in a thermal model by η/n c =e -m/T <1, and this fact reduces any Bose-Einstein correction effects in the number and number fluctuation of pions. Fluctuations can be much larger than Poisson in the pion laser model and for a negative binomial description. The clan representation of the negative binomial distribution due to Van Hove and Giovannini is discussed using the present description. Applications to CERN/NA44 and CERN/NA49 data are discussed in terms of the relativistic hydrodynamic model. copyright 1998 The American Physical Society

INVESTIGATION OF INFLUENCE OF ENCODING FUNCTION COMPLEXITY ON DISTRIBUTION OF ERROR MASKING PROBABILITY

Directory of Open Access Journals (Sweden)

A. B. Levina

2016-03-01

Full Text Available Error detection codes are mechanisms that enable robust delivery of data in unreliable communication channels and devices. Unreliable channels and devices are error-prone objects. Respectively, error detection codes allow detecting such errors. There are two classes of error detecting codes - classical codes and security-oriented codes. The classical codes have high percentage of detected errors; however, they have a high probability to miss an error in algebraic manipulation. In order, security-oriented codes are codes with a small Hamming distance and high protection to algebraic manipulation. The probability of error masking is a fundamental parameter of security-oriented codes. A detailed study of this parameter allows analyzing the behavior of the error-correcting code in the case of error injection in the encoding device. In order, the complexity of the encoding function plays an important role in the security-oriented codes. Encoding functions with less computational complexity and a low probability of masking are the best protection of encoding device against malicious acts. This paper investigates the influence of encoding function complexity on the error masking probability distribution. It will be shownthat the more complex encoding function reduces the maximum of error masking probability. It is also shown in the paper that increasing of the function complexity changes the error masking probability distribution. In particular, increasing of computational complexity decreases the difference between the maximum and average value of the error masking probability. Our resultshave shown that functions with greater complexity have smoothed maximums of error masking probability, which significantly complicates the analysis of error-correcting code by attacker. As a result, in case of complex encoding function the probability of the algebraic manipulation is reduced. The paper discusses an approach how to measure the error masking

Influences of variables on ship collision probability in a Bayesian belief network model

International Nuclear Information System (INIS)

Hänninen, Maria; Kujala, Pentti

2012-01-01

The influences of the variables in a Bayesian belief network model for estimating the role of human factors on ship collision probability in the Gulf of Finland are studied for discovering the variables with the largest influences and for examining the validity of the network. The change in the so-called causation probability is examined while observing each state of the network variables and by utilizing sensitivity and mutual information analyses. Changing course in an encounter situation is the most influential variable in the model, followed by variables such as the Officer of the Watch's action, situation assessment, danger detection, personal condition and incapacitation. The least influential variables are the other distractions on bridge, the bridge view, maintenance routines and the officer's fatigue. In general, the methods are found to agree on the order of the model variables although some disagreements arise due to slightly dissimilar approaches to the concept of variable influence. The relative values and the ranking of variables based on the values are discovered to be more valuable than the actual numerical values themselves. Although the most influential variables seem to be plausible, there are some discrepancies between the indicated influences in the model and literature. Thus, improvements are suggested to the network.

Quantification of a decision-making failure probability of the accident management using cognitive analysis model

Energy Technology Data Exchange (ETDEWEB)

Yoshida, Yoshitaka; Ohtani, Masanori [Institute of Nuclear Safety System, Inc., Mihama, Fukui (Japan); Fujita, Yushi [TECNOVA Corp., Tokyo (Japan)

2002-09-01

In the nuclear power plant, much knowledge is acquired through probabilistic safety assessment (PSA) of a severe accident, and accident management (AM) is prepared. It is necessary to evaluate the effectiveness of AM using the decision-making failure probability of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipments in PSA. However, there has been no suitable qualification method for PSA so far to obtain the decision-making failure probability, because the decision-making failure of an emergency organization treats the knowledge based error. In this work, we developed a new method for quantification of the decision-making failure probability of an emergency organization using cognitive analysis model, which decided an AM strategy, in a nuclear power plant at the severe accident, and tried to apply it to a typical pressurized water reactor (PWR) plant. As a result: (1) It could quantify the decision-making failure probability adjusted to PSA for general analysts, who do not necessarily possess professional human factors knowledge, by choosing the suitable value of a basic failure probability and an error-factor. (2) The decision-making failure probabilities of six AMs were in the range of 0.23 to 0.41 using the screening evaluation method and in the range of 0.10 to 0.19 using the detailed evaluation method as the result of trial evaluation based on severe accident analysis of a typical PWR plant, and a result of sensitivity analysis of the conservative assumption, failure probability decreased about 50%. (3) The failure probability using the screening evaluation method exceeded that using detailed evaluation method by 99% of probability theoretically, and the failure probability of AM in this study exceeded 100%. From this result, it was shown that the decision-making failure probability was more conservative than the detailed evaluation method, and the screening evaluation method satisfied

Quantification of a decision-making failure probability of the accident management using cognitive analysis model

International Nuclear Information System (INIS)

Yoshida, Yoshitaka; Ohtani, Masanori; Fujita, Yushi

2002-01-01

In the nuclear power plant, much knowledge is acquired through probabilistic safety assessment (PSA) of a severe accident, and accident management (AM) is prepared. It is necessary to evaluate the effectiveness of AM using the decision-making failure probability of an emergency organization, operation failure probability of operators, success criteria of AM and reliability of AM equipments in PSA. However, there has been no suitable qualification method for PSA so far to obtain the decision-making failure probability, because the decision-making failure of an emergency organization treats the knowledge based error. In this work, we developed a new method for quantification of the decision-making failure probability of an emergency organization using cognitive analysis model, which decided an AM strategy, in a nuclear power plant at the severe accident, and tried to apply it to a typical pressurized water reactor (PWR) plant. As a result: (1) It could quantify the decision-making failure probability adjusted to PSA for general analysts, who do not necessarily possess professional human factors knowledge, by choosing the suitable value of a basic failure probability and an error-factor. (2) The decision-making failure probabilities of six AMs were in the range of 0.23 to 0.41 using the screening evaluation method and in the range of 0.10 to 0.19 using the detailed evaluation method as the result of trial evaluation based on severe accident analysis of a typical PWR plant, and a result of sensitivity analysis of the conservative assumption, failure probability decreased about 50%. (3) The failure probability using the screening evaluation method exceeded that using detailed evaluation method by 99% of probability theoretically, and the failure probability of AM in this study exceeded 100%. From this result, it was shown that the decision-making failure probability was more conservative than the detailed evaluation method, and the screening evaluation method satisfied

A cellular automata model of traffic flow with variable probability of randomization

International Nuclear Information System (INIS)

Zheng Wei-Fan; Zhang Ji-Ye

2015-01-01

Research on the stochastic behavior of traffic flow is important to understand the intrinsic evolution rules of a traffic system. By introducing an interactional potential of vehicles into the randomization step, an improved cellular automata traffic flow model with variable probability of randomization is proposed in this paper. In the proposed model, the driver is affected by the interactional potential of vehicles before him, and his decision-making process is related to the interactional potential. Compared with the traditional cellular automata model, the modeling is more suitable for the driver’s random decision-making process based on the vehicle and traffic situations in front of him in actual traffic. From the improved model, the fundamental diagram (flow–density relationship) is obtained, and the detailed high-density traffic phenomenon is reproduced through numerical simulation. (paper)

Collision Probability Analysis

DEFF Research Database (Denmark)

Hansen, Peter Friis; Pedersen, Preben Terndrup

1998-01-01

It is the purpose of this report to apply a rational model for prediction of ship-ship collision probabilities as function of the ship and the crew characteristics and the navigational environment for MS Dextra sailing on a route between Cadiz and the Canary Islands.The most important ship and crew...... characteristics are: ship speed, ship manoeuvrability, the layout of the navigational bridge, the radar system, the number and the training of navigators, the presence of a look out etc. The main parameters affecting the navigational environment are ship traffic density, probability distributions of wind speeds...... probability, i.e. a study of the navigator's role in resolving critical situations, a causation factor is derived as a second step.The report documents the first step in a probabilistic collision damage analysis. Future work will inlcude calculation of energy released for crushing of structures giving...

Generalized Probability-Probability Plots

NARCIS (Netherlands)

Mushkudiani, N.A.; Einmahl, J.H.J.

2004-01-01

We introduce generalized Probability-Probability (P-P) plots in order to study the one-sample goodness-of-fit problem and the two-sample problem, for real valued data.These plots, that are constructed by indexing with the class of closed intervals, globally preserve the properties of classical P-P

Quantum Probabilities as Behavioral Probabilities

Directory of Open Access Journals (Sweden)

Vyacheslav I. Yukalov

2017-03-01

Full Text Available We demonstrate that behavioral probabilities of human decision makers share many common features with quantum probabilities. This does not imply that humans are some quantum objects, but just shows that the mathematics of quantum theory is applicable to the description of human decision making. The applicability of quantum rules for describing decision making is connected with the nontrivial process of making decisions in the case of composite prospects under uncertainty. Such a process involves deliberations of a decision maker when making a choice. In addition to the evaluation of the utilities of considered prospects, real decision makers also appreciate their respective attractiveness. Therefore, human choice is not based solely on the utility of prospects, but includes the necessity of resolving the utility-attraction duality. In order to justify that human consciousness really functions similarly to the rules of quantum theory, we develop an approach defining human behavioral probabilities as the probabilities determined by quantum rules. We show that quantum behavioral probabilities of humans do not merely explain qualitatively how human decisions are made, but they predict quantitative values of the behavioral probabilities. Analyzing a large set of empirical data, we find good quantitative agreement between theoretical predictions and observed experimental data.

Classical probability model for Bell inequality

International Nuclear Information System (INIS)

Khrennikov, Andrei

2014-01-01

We show that by taking into account randomness of realization of experimental contexts it is possible to construct common Kolmogorov space for data collected for these contexts, although they can be incompatible. We call such a construction 'Kolmogorovization' of contextuality. This construction of common probability space is applied to Bell's inequality. It is well known that its violation is a consequence of collecting statistical data in a few incompatible experiments. In experiments performed in quantum optics contexts are determined by selections of pairs of angles (θ i ,θ ' j ) fixing orientations of polarization beam splitters. Opposite to the common opinion, we show that statistical data corresponding to measurements of polarizations of photons in the singlet state, e.g., in the form of correlations, can be described in the classical probabilistic framework. The crucial point is that in constructing the common probability space one has to take into account not only randomness of the source (as Bell did), but also randomness of context-realizations (in particular, realizations of pairs of angles (θ i , θ ' j )). One may (but need not) say that randomness of 'free will' has to be accounted for.

Modeling spatial variability of sand-lenses in clay till settings using transition probability and multiple-point geostatistics

DEFF Research Database (Denmark)

Kessler, Timo Christian; Nilsson, Bertel; Klint, Knud Erik

2010-01-01

(TPROGS) of alternating geological facies. The second method, multiple-point statistics, uses training images to estimate the conditional probability of sand-lenses at a certain location. Both methods respect field observations such as local stratigraphy, however, only the multiple-point statistics can...... of sand-lenses in clay till. Sand-lenses mainly account for horizontal transport and are prioritised in this study. Based on field observations, the distribution has been modeled using two different geostatistical approaches. One method uses a Markov chain model calculating the transition probabilities...

Probability Aggregates in Probability Answer Set Programming

OpenAIRE

Saad, Emad

2013-01-01

Probability answer set programming is a declarative programming that has been shown effective for representing and reasoning about a variety of probability reasoning tasks. However, the lack of probability aggregates, e.g. {\\em expected values}, in the language of disjunctive hybrid probability logic programs (DHPP) disallows the natural and concise representation of many interesting problems. In this paper, we extend DHPP to allow arbitrary probability aggregates. We introduce two types of p...

Probability modeling of high flow extremes in Yingluoxia watershed, the upper reaches of Heihe River basin

Science.gov (United States)

Li, Zhanling; Li, Zhanjie; Li, Chengcheng

2014-05-01

Probability modeling of hydrological extremes is one of the major research areas in hydrological science. Most basins in humid and semi-humid south and east of China are concerned for probability modeling analysis of high flow extremes. While, for the inland river basin which occupies about 35% of the country area, there is a limited presence of such studies partly due to the limited data availability and a relatively low mean annual flow. The objective of this study is to carry out probability modeling of high flow extremes in the upper reach of Heihe River basin, the second largest inland river basin in China, by using the peak over threshold (POT) method and Generalized Pareto Distribution (GPD), in which the selection of threshold and inherent assumptions for POT series are elaborated in details. For comparison, other widely used probability distributions including generalized extreme value (GEV), Lognormal, Log-logistic and Gamma are employed as well. Maximum likelihood estimate is used for parameter estimations. Daily flow data at Yingluoxia station from 1978 to 2008 are used. Results show that, synthesizing the approaches of mean excess plot, stability features of model parameters, return level plot and the inherent independence assumption of POT series, an optimum threshold of 340m3/s is finally determined for high flow extremes in Yingluoxia watershed. The resulting POT series is proved to be stationary and independent based on Mann-Kendall test, Pettitt test and autocorrelation test. In terms of Kolmogorov-Smirnov test, Anderson-Darling test and several graphical diagnostics such as quantile and cumulative density function plots, GPD provides the best fit to high flow extremes in the study area. The estimated high flows for long return periods demonstrate that, as the return period increasing, the return level estimates are probably more uncertain. The frequency of high flow extremes exhibits a very slight but not significant decreasing trend from 1978 to

Influence of early neurological complications on clinical outcome following lung transplant.

Science.gov (United States)

Gamez, Josep; Salvado, Maria; Martinez-de La Ossa, Alejandro; Deu, Maria; Romero, Laura; Roman, Antonio; Sacanell, Judith; Laborda, Cesar; Rochera, Isabel; Nadal, Miriam; Carmona, Francesc; Santamarina, Estevo; Raguer, Nuria; Canela, Merce; Solé, Joan

2017-01-01

Neurological complications after lung transplantation are common. The full spectrum of neurological complications and their impact on clinical outcomes has not been extensively studied. We investigated the neurological incidence of complications, categorized according to whether they affected the central, peripheral or autonomic nervous systems, in a series of 109 patients undergoing lung transplantation at our center between January 1 2013 and December 31 2014. Fifty-one patients (46.8%) presented at least one neurological complication. Critical illness polyneuropathy-myopathy (31 cases) and phrenic nerve injury (26 cases) were the two most prevalent complications. These two neuromuscular complications lengthened hospital stays by a median period of 35.5 and 32.5 days respectively. However, neurological complications did not affect patients' survival. The real incidence of neurological complications among lung transplant recipients is probably underestimated. They usually appear in the first two months after surgery. Despite not affecting mortality, they do affect the mean length of hospital stay, and especially the time spent in the Intensive Care Unit. We found no risk factor for neurological complications except for long operating times, ischemic time and need for transfusion. It is necessary to develop programs for the prevention and early recognition of these complications, and the prevention of their precipitant and risk factors.

Determination of probability density functions for parameters in the Munson-Dawson model for creep behavior of salt

International Nuclear Information System (INIS)

Pfeifle, T.W.; Mellegard, K.D.; Munson, D.E.

1992-10-01

The modified Munson-Dawson (M-D) constitutive model that describes the creep behavior of salt will be used in performance assessment calculations to assess compliance of the Waste Isolation Pilot Plant (WIPP) facility with requirements governing the disposal of nuclear waste. One of these standards requires that the uncertainty of future states of the system, material model parameters, and data be addressed in the performance assessment models. This paper presents a method in which measurement uncertainty and the inherent variability of the material are characterized by treating the M-D model parameters as random variables. The random variables can be described by appropriate probability distribution functions which then can be used in Monte Carlo or structural reliability analyses. Estimates of three random variables in the M-D model were obtained by fitting a scalar form of the model to triaxial compression creep data generated from tests of WIPP salt. Candidate probability distribution functions for each of the variables were then fitted to the estimates and their relative goodness-of-fit tested using the Kolmogorov-Smirnov statistic. A sophisticated statistical software package obtained from BMDP Statistical Software, Inc. was used in the M-D model fitting. A separate software package, STATGRAPHICS, was used in fitting the candidate probability distribution functions to estimates of the variables. Skewed distributions, i.e., lognormal and Weibull, were found to be appropriate for the random variables analyzed

Toward Big Data Analytics: Review of Predictive Models in Management of Diabetes and Its Complications.

Science.gov (United States)

Cichosz, Simon Lebech; Johansen, Mette Dencker; Hejlesen, Ole

2015-10-14

Diabetes is one of the top priorities in medical science and health care management, and an abundance of data and information is available on these patients. Whether data stem from statistical models or complex pattern recognition models, they may be fused into predictive models that combine patient information and prognostic outcome results. Such knowledge could be used in clinical decision support, disease surveillance, and public health management to improve patient care. Our aim was to review the literature and give an introduction to predictive models in screening for and the management of prevalent short- and long-term complications in diabetes. Predictive models have been developed for management of diabetes and its complications, and the number of publications on such models has been growing over the past decade. Often multiple logistic or a similar linear regression is used for prediction model development, possibly owing to its transparent functionality. Ultimately, for prediction models to prove useful, they must demonstrate impact, namely, their use must generate better patient outcomes. Although extensive effort has been put in to building these predictive models, there is a remarkable scarcity of impact studies. © 2015 Diabetes Technology Society.

Developing a Mathematical Model for Scheduling and Determining Success Probability of Research Projects Considering Complex-Fuzzy Networks

Directory of Open Access Journals (Sweden)

Gholamreza Norouzi

2015-01-01

Full Text Available In project management context, time management is one of the most important factors affecting project success. This paper proposes a new method to solve research project scheduling problems (RPSP containing Fuzzy Graphical Evaluation and Review Technique (FGERT networks. Through the deliverables of this method, a proper estimation of project completion time (PCT and success probability can be achieved. So algorithms were developed to cover all features of the problem based on three main parameters “duration, occurrence probability, and success probability.” These developed algorithms were known as PR-FGERT (Parallel and Reversible-Fuzzy GERT networks. The main provided framework includes simplifying the network of project and taking regular steps to determine PCT and success probability. Simplifications include (1 equivalent making of parallel and series branches in fuzzy network considering the concepts of probabilistic nodes, (2 equivalent making of delay or reversible-to-itself branches and impact of changing the parameters of time and probability based on removing related branches, (3 equivalent making of simple and complex loops, and (4 an algorithm that was provided to resolve no-loop fuzzy network, after equivalent making. Finally, the performance of models was compared with existing methods. The results showed proper and real performance of models in comparison with existing methods.

A combined Importance Sampling and Kriging reliability method for small failure probabilities with time-demanding numerical models

International Nuclear Information System (INIS)

Echard, B.; Gayton, N.; Lemaire, M.; Relun, N.

2013-01-01

Applying reliability methods to a complex structure is often delicate for two main reasons. First, such a structure is fortunately designed with codified rules leading to a large safety margin which means that failure is a small probability event. Such a probability level is difficult to assess efficiently. Second, the structure mechanical behaviour is modelled numerically in an attempt to reproduce the real response and numerical model tends to be more and more time-demanding as its complexity is increased to improve accuracy and to consider particular mechanical behaviour. As a consequence, performing a large number of model computations cannot be considered in order to assess the failure probability. To overcome these issues, this paper proposes an original and easily implementable method called AK-IS for active learning and Kriging-based Importance Sampling. This new method is based on the AK-MCS algorithm previously published by Echard et al. [AK-MCS: an active learning reliability method combining Kriging and Monte Carlo simulation. Structural Safety 2011;33(2):145–54]. It associates the Kriging metamodel and its advantageous stochastic property with the Importance Sampling method to assess small failure probabilities. It enables the correction or validation of the FORM approximation with only a very few mechanical model computations. The efficiency of the method is, first, proved on two academic applications. It is then conducted for assessing the reliability of a challenging aerospace case study submitted to fatigue.

Fast Outage Probability Simulation for FSO Links with a Generalized Pointing Error Model

KAUST Repository

Ben Issaid, Chaouki

2017-02-07

Over the past few years, free-space optical (FSO) communication has gained significant attention. In fact, FSO can provide cost-effective and unlicensed links, with high-bandwidth capacity and low error rate, making it an exciting alternative to traditional wireless radio-frequency communication systems. However, the system performance is affected not only by the presence of atmospheric turbulences, which occur due to random fluctuations in the air refractive index but also by the existence of pointing errors. Metrics, such as the outage probability which quantifies the probability that the instantaneous signal-to-noise ratio is smaller than a given threshold, can be used to analyze the performance of this system. In this work, we consider weak and strong turbulence regimes, and we study the outage probability of an FSO communication system under a generalized pointing error model with both a nonzero boresight component and different horizontal and vertical jitter effects. More specifically, we use an importance sampling approach which is based on the exponential twisting technique to offer fast and accurate results.

Fixation Probability in a Haploid-Diploid Population.

Science.gov (United States)

Bessho, Kazuhiro; Otto, Sarah P

2017-01-01

Classical population genetic theory generally assumes either a fully haploid or fully diploid life cycle. However, many organisms exhibit more complex life cycles, with both free-living haploid and diploid stages. Here we ask what the probability of fixation is for selected alleles in organisms with haploid-diploid life cycles. We develop a genetic model that considers the population dynamics using both the Moran model and Wright-Fisher model. Applying a branching process approximation, we obtain an accurate fixation probability assuming that the population is large and the net effect of the mutation is beneficial. We also find the diffusion approximation for the fixation probability, which is accurate even in small populations and for deleterious alleles, as long as selection is weak. These fixation probabilities from branching process and diffusion approximations are similar when selection is weak for beneficial mutations that are not fully recessive. In many cases, particularly when one phase predominates, the fixation probability differs substantially for haploid-diploid organisms compared to either fully haploid or diploid species. Copyright © 2017 by the Genetics Society of America.

Simple Urban Simulation Atop Complicated Models: Multi-Scale Equation-Free Computing of Sprawl Using Geographic Automata

Directory of Open Access Journals (Sweden)

Yu Zou

2013-07-01

Full Text Available Reconciling competing desires to build urban models that can be simple and complicated is something of a grand challenge for urban simulation. It also prompts difficulties in many urban policy situations, such as urban sprawl, where simple, actionable ideas may need to be considered in the context of the messily complex and complicated urban processes and phenomena that work within cities. In this paper, we present a novel architecture for achieving both simple and complicated realizations of urban sprawl in simulation. Fine-scale simulations of sprawl geography are run using geographic automata to represent the geographical drivers of sprawl in intricate detail and over fine resolutions of space and time. We use Equation-Free computing to deploy population as a coarse observable of sprawl, which can be leveraged to run automata-based models as short-burst experiments within a meta-simulation framework.

Uncovering the Best Skill Multimap by Constraining the Error Probabilities of the Gain-Loss Model

Science.gov (United States)

Anselmi, Pasquale; Robusto, Egidio; Stefanutti, Luca

2012-01-01

The Gain-Loss model is a probabilistic skill multimap model for assessing learning processes. In practical applications, more than one skill multimap could be plausible, while none corresponds to the true one. The article investigates whether constraining the error probabilities is a way of uncovering the best skill assignment among a number of…

Finite element model updating of concrete structures based on imprecise probability

Science.gov (United States)

Biswal, S.; Ramaswamy, A.

2017-09-01

Imprecise probability based methods are developed in this study for the parameter estimation, in finite element model updating for concrete structures, when the measurements are imprecisely defined. Bayesian analysis using Metropolis Hastings algorithm for parameter estimation is generalized to incorporate the imprecision present in the prior distribution, in the likelihood function, and in the measured responses. Three different cases are considered (i) imprecision is present in the prior distribution and in the measurements only, (ii) imprecision is present in the parameters of the finite element model and in the measurement only, and (iii) imprecision is present in the prior distribution, in the parameters of the finite element model, and in the measurements. Procedures are also developed for integrating the imprecision in the parameters of the finite element model, in the finite element software Abaqus. The proposed methods are then verified against reinforced concrete beams and prestressed concrete beams tested in our laboratory as part of this study.

Identifying Changes in the Probability of High Temperature, High Humidity Heat Wave Events

Science.gov (United States)

Ballard, T.; Diffenbaugh, N. S.

2016-12-01

Understanding how heat waves will respond to climate change is critical for adequate planning and adaptation. While temperature is the primary determinant of heat wave severity, humidity has been shown to play a key role in heat wave intensity with direct links to human health and safety. Here we investigate the individual contributions of temperature and specific humidity to extreme heat wave conditions in recent decades. Using global NCEP-DOE Reanalysis II daily data, we identify regional variability in the joint probability distribution of humidity and temperature. We also identify a statistically significant positive trend in humidity over the eastern U.S. during heat wave events, leading to an increased probability of high humidity, high temperature events. The extent to which we can expect this trend to continue under climate change is complicated due to variability between CMIP5 models, in particular among projections of humidity. However, our results support the notion that heat wave dynamics are characterized by more than high temperatures alone, and understanding and quantifying the various components of the heat wave system is crucial for forecasting future impacts.

Characterization of vascular complications in experimental model of fructose-induced metabolic syndrome.

Science.gov (United States)

El-Bassossy, Hany M; Dsokey, Nora; Fahmy, Ahmed

2014-12-01

Vascular dysfunction is an important complication associated with metabolic syndrome (MS). Here we fully characterized vascular complications in a rat model of fructose-induced MS. MS was induced by adding fructose (10%) to drinking water to male Wistar rats of 6 weeks age. Blood pressure (BP) and isolated aorta responses phenylephrine (PE), KCl, acetylcholine (ACh), and sodium nitroprusside (SNP) were recorded after 6, 9, and 12 weeks of fructose administration. In addition, serum levels of glucose, insulin, uric acid, tumor necrosis factor α (TNFα), lipids, advanced glycation end products (AGEs), and arginase activity were determined. Furthermore, aortic reactive oxygen species (ROS) generation, hemeoxygenase-1 expression, and collagen deposition were examined. Fructose administration resulted in a significant hyperinslinemia after 6 weeks which continued for 12 weeks. It was also associated with a significant increase in BP after 6 weeks which was stable for 12 weeks. Aorta isolated from MS animals showed exaggerated contractility to PE and KCl and impaired relaxation to ACh compared with control after 6 weeks which were clearer at 12 weeks of fructose administration. In addition, MS animals showed significant increases in serum levels of lipids, uric acid, AGEs, TNFα, and arginase enzyme activity after 12 weeks of fructose administration. Furthermore, aortae isolated from MS animals were characterized by increased ROS generation and collagen deposition. In conclusion, adding fructose (10%) to drinking water produces a model of MS with vascular complications after 12 weeks that are characterized by insulin resistance, hypertension, disturbed vascular reactivity and structure, hyperuricemia, dyslipidemia, and low-grade inflammation.

Probability of Detection (POD) as a statistical model for the validation of qualitative methods.

Science.gov (United States)

Wehling, Paul; LaBudde, Robert A; Brunelle, Sharon L; Nelson, Maria T

2011-01-01

A statistical model is presented for use in validation of qualitative methods. This model, termed Probability of Detection (POD), harmonizes the statistical concepts and parameters between quantitative and qualitative method validation. POD characterizes method response with respect to concentration as a continuous variable. The POD model provides a tool for graphical representation of response curves for qualitative methods. In addition, the model allows comparisons between candidate and reference methods, and provides calculations of repeatability, reproducibility, and laboratory effects from collaborative study data. Single laboratory study and collaborative study examples are given.

Bayesian selection of misspecified models is overconfident and may cause spurious posterior probabilities for phylogenetic trees.

Science.gov (United States)

Yang, Ziheng; Zhu, Tianqi

2018-02-20

The Bayesian method is noted to produce spuriously high posterior probabilities for phylogenetic trees in analysis of large datasets, but the precise reasons for this overconfidence are unknown. In general, the performance of Bayesian selection of misspecified models is poorly understood, even though this is of great scientific interest since models are never true in real data analysis. Here we characterize the asymptotic behavior of Bayesian model selection and show that when the competing models are equally wrong, Bayesian model selection exhibits surprising and polarized behaviors in large datasets, supporting one model with full force while rejecting the others. If one model is slightly less wrong than the other, the less wrong model will eventually win when the amount of data increases, but the method may become overconfident before it becomes reliable. We suggest that this extreme behavior may be a major factor for the spuriously high posterior probabilities for evolutionary trees. The philosophical implications of our results to the application of Bayesian model selection to evaluate opposing scientific hypotheses are yet to be explored, as are the behaviors of non-Bayesian methods in similar situations.

Model-assisted probability of detection of flaws in aluminum blocks using polynomial chaos expansions

Science.gov (United States)

Du, Xiaosong; Leifsson, Leifur; Grandin, Robert; Meeker, William; Roberts, Ronald; Song, Jiming

2018-04-01

Probability of detection (POD) is widely used for measuring reliability of nondestructive testing (NDT) systems. Typically, POD is determined experimentally, while it can be enhanced by utilizing physics-based computational models in combination with model-assisted POD (MAPOD) methods. With the development of advanced physics-based methods, such as ultrasonic NDT testing, the empirical information, needed for POD methods, can be reduced. However, performing accurate numerical simulations can be prohibitively time-consuming, especially as part of stochastic analysis. In this work, stochastic surrogate models for computational physics-based measurement simulations are developed for cost savings of MAPOD methods while simultaneously ensuring sufficient accuracy. The stochastic surrogate is used to propagate the random input variables through the physics-based simulation model to obtain the joint probability distribution of the output. The POD curves are then generated based on those results. Here, the stochastic surrogates are constructed using non-intrusive polynomial chaos (NIPC) expansions. In particular, the NIPC methods used are the quadrature, ordinary least-squares (OLS), and least-angle regression sparse (LARS) techniques. The proposed approach is demonstrated on the ultrasonic testing simulation of a flat bottom hole flaw in an aluminum block. The results show that the stochastic surrogates have at least two orders of magnitude faster convergence on the statistics than direct Monte Carlo sampling (MCS). Moreover, the evaluation of the stochastic surrogate models is over three orders of magnitude faster than the underlying simulation model for this case, which is the UTSim2 model.

Individual model evaluation and probabilistic weighting of models

International Nuclear Information System (INIS)

Atwood, C.L.

1994-01-01

This note stresses the importance of trying to assess the accuracy of each model individually. Putting a Bayesian probability distribution on a population of models faces conceptual and practical complications, and apparently can come only after the work of evaluating the individual models. Moreover, the primary issue is open-quotes How good is this modelclose quotes? Therefore, the individual evaluations are first in both chronology and importance. They are not easy, but some ideas are given here on how to perform them

Probability distributions in conservative energy exchange models of multiple interacting agents

International Nuclear Information System (INIS)

Scafetta, Nicola; West, Bruce J

2007-01-01

Herein we study energy exchange models of multiple interacting agents that conserve energy in each interaction. The models differ regarding the rules that regulate the energy exchange and boundary effects. We find a variety of stochastic behaviours that manifest energy equilibrium probability distributions of different types and interaction rules that yield not only the exponential distributions such as the familiar Maxwell-Boltzmann-Gibbs distribution of an elastically colliding ideal particle gas, but also uniform distributions, truncated exponential distributions, Gaussian distributions, Gamma distributions, inverse power law distributions, mixed exponential and inverse power law distributions, and evolving distributions. This wide variety of distributions should be of value in determining the underlying mechanisms generating the statistical properties of complex phenomena including those to be found in complex chemical reactions

Logic, probability, and human reasoning.

Science.gov (United States)

Johnson-Laird, P N; Khemlani, Sangeet S; Goodwin, Geoffrey P

2015-04-01

This review addresses the long-standing puzzle of how logic and probability fit together in human reasoning. Many cognitive scientists argue that conventional logic cannot underlie deductions, because it never requires valid conclusions to be withdrawn - not even if they are false; it treats conditional assertions implausibly; and it yields many vapid, although valid, conclusions. A new paradigm of probability logic allows conclusions to be withdrawn and treats conditionals more plausibly, although it does not address the problem of vapidity. The theory of mental models solves all of these problems. It explains how people reason about probabilities and postulates that the machinery for reasoning is itself probabilistic. Recent investigations accordingly suggest a way to integrate probability and deduction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Negative probability in the framework of combined probability

OpenAIRE

Burgin, Mark

2013-01-01

Negative probability has found diverse applications in theoretical physics. Thus, construction of sound and rigorous mathematical foundations for negative probability is important for physics. There are different axiomatizations of conventional probability. So, it is natural that negative probability also has different axiomatic frameworks. In the previous publications (Burgin, 2009; 2010), negative probability was mathematically formalized and rigorously interpreted in the context of extende...

The limiting conditional probability distribution in a stochastic model of T cell repertoire maintenance.

Science.gov (United States)

Stirk, Emily R; Lythe, Grant; van den Berg, Hugo A; Hurst, Gareth A D; Molina-París, Carmen

2010-04-01

The limiting conditional probability distribution (LCD) has been much studied in the field of mathematical biology, particularly in the context of epidemiology and the persistence of epidemics. However, it has not yet been applied to the immune system. One of the characteristic features of the T cell repertoire is its diversity. This diversity declines in old age, whence the concepts of extinction and persistence are also relevant to the immune system. In this paper we model T cell repertoire maintenance by means of a continuous-time birth and death process on the positive integers, where the origin is an absorbing state. We show that eventual extinction is guaranteed. The late-time behaviour of the process before extinction takes place is modelled by the LCD, which we prove always exists for the process studied here. In most cases, analytic expressions for the LCD cannot be computed but the probability distribution may be approximated by means of the stationary probability distributions of two related processes. We show how these approximations are related to the LCD of the original process and use them to study the LCD in two special cases. We also make use of the large N expansion to derive a further approximation to the LCD. The accuracy of the various approximations is then analysed. (c) 2009 Elsevier Inc. All rights reserved.

Fundamentals of applied probability and random processes

CERN Document Server

Ibe, Oliver

2014-01-01

The long-awaited revision of Fundamentals of Applied Probability and Random Processes expands on the central components that made the first edition a classic. The title is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability t

Application of the Tripartite Model to a Complicated Sample of Residential Youth with Externalizing Problems

Science.gov (United States)

Chin, Eu Gene; Ebesutani, Chad; Young, John

2013-01-01

The tripartite model of anxiety and depression has received strong support among child and adolescent populations. Clinical samples of children and adolescents in these studies, however, have usually been referred for treatment of anxiety and depression. This study investigated the fit of the tripartite model with a complicated sample of…

The HYDROMED model and its application to semi-arid Mediterranean catchments with hill reservoirs 3: Reservoir storage capacity and probability of failure model

Directory of Open Access Journals (Sweden)

R. Ragab

2001-01-01

Full Text Available This paper addresses the issue of "what reservoir storage capacity is required to maintain a yield with a given probability of failure?". It is an important issue in terms of construction and cost. HYDROMED offers a solution based on the modified Gould probability matrix method. This method has the advantage of sampling all years data without reference to the sequence and is therefore particularly suitable for catchments with patchy data. In the HYDROMED model, the probability of failure is calculated on a monthly basis. The model has been applied to the El-Gouazine catchment in Tunisia using a long rainfall record from Kairouan together with the estimated Hortonian runoff, class A pan evaporation data and estimated abstraction data. Generally, the probability of failure differed from winter to summer. Generally, the probability of failure approaches zero when the reservoir capacity is 500,000 m3. The 25% probability of failure (75% success is achieved with a reservoir capacity of 58,000 m3 in June and 95,000 m3 in January. The probability of failure for a 240,000 m3 capacity reservoir (closer to storage capacity of El-Gouazine 233,000 m3, is approximately 5% in November, December and January, 3% in March, and 1.1% in May and June. Consequently there is no high risk of El-Gouazine being unable to meet its requirements at a capacity of 233,000 m3. Subsequently the benefit, in terms of probability of failure, by increasing the reservoir volume of El-Gouazine to greater than the 250,000 m3 is not high. This is important for the design engineers and the funding organizations. However, the analysis is based on the existing water abstraction policy, absence of siltation rate data and on the assumption that the present climate will prevail during the lifetime of the reservoir. Should these conditions change, a new analysis should be carried out. Keywords: HYDROMED, reservoir, storage capacity, probability of failure, Mediterranean

Probabilities in quantum cosmological models: A decoherent histories analysis using a complex potential

International Nuclear Information System (INIS)

Halliwell, J. J.

2009-01-01

In the quantization of simple cosmological models (minisuperspace models) described by the Wheeler-DeWitt equation, an important step is the construction, from the wave function, of a probability distribution answering various questions of physical interest, such as the probability of the system entering a given region of configuration space at any stage in its entire history. A standard but heuristic procedure is to use the flux of (components of) the wave function in a WKB approximation. This gives sensible semiclassical results but lacks an underlying operator formalism. In this paper, we address the issue of constructing probability distributions linked to the Wheeler-DeWitt equation using the decoherent histories approach to quantum theory. The key step is the construction of class operators characterizing questions of physical interest. Taking advantage of a recent decoherent histories analysis of the arrival time problem in nonrelativistic quantum mechanics, we show that the appropriate class operators in quantum cosmology are readily constructed using a complex potential. The class operator for not entering a region of configuration space is given by the S matrix for scattering off a complex potential localized in that region. We thus derive the class operators for entering one or more regions in configuration space. The class operators commute with the Hamiltonian, have a sensible classical limit, and are closely related to an intersection number operator. The definitions of class operators given here handle the key case in which the underlying classical system has multiple crossings of the boundaries of the regions of interest. We show that oscillatory WKB solutions to the Wheeler-DeWitt equation give approximate decoherence of histories, as do superpositions of WKB solutions, as long as the regions of configuration space are sufficiently large. The corresponding probabilities coincide, in a semiclassical approximation, with standard heuristic procedures

Characteristic length of the knotting probability revisited

International Nuclear Information System (INIS)

Uehara, Erica; Deguchi, Tetsuo

2015-01-01

We present a self-avoiding polygon (SAP) model for circular DNA in which the radius of impermeable cylindrical segments corresponds to the screening length of double-stranded DNA surrounded by counter ions. For the model we evaluate the probability for a generated SAP with N segments having a given knot K through simulation. We call it the knotting probability of a knot K with N segments for the SAP model. We show that when N is large the most significant factor in the knotting probability is given by the exponentially decaying part exp(−N/N K ), where the estimates of parameter N K are consistent with the same value for all the different knots we investigated. We thus call it the characteristic length of the knotting probability. We give formulae expressing the characteristic length as a function of the cylindrical radius r ex , i.e. the screening length of double-stranded DNA. (paper)

Precipitation intensity probability distribution modelling for hydrological and construction design purposes

International Nuclear Information System (INIS)

Koshinchanov, Georgy; Dimitrov, Dobri

2008-01-01

The characteristics of rainfall intensity are important for many purposes, including design of sewage and drainage systems, tuning flood warning procedures, etc. Those estimates are usually statistical estimates of the intensity of precipitation realized for certain period of time (e.g. 5, 10 min., etc) with different return period (e.g. 20, 100 years, etc). The traditional approach in evaluating the mentioned precipitation intensities is to process the pluviometer's records and fit probability distribution to samples of intensities valid for certain locations ore regions. Those estimates further become part of the state regulations to be used for various economic activities. Two problems occur using the mentioned approach: 1. Due to various factors the climate conditions are changed and the precipitation intensity estimates need regular update; 2. As far as the extremes of the probability distribution are of particular importance for the practice, the methodology of the distribution fitting needs specific attention to those parts of the distribution. The aim of this paper is to make review of the existing methodologies for processing the intensive rainfalls and to refresh some of the statistical estimates for the studied areas. The methodologies used in Bulgaria for analyzing the intensive rainfalls and produce relevant statistical estimates: - The method of the maximum intensity, used in the National Institute of Meteorology and Hydrology to process and decode the pluviometer's records, followed by distribution fitting for each precipitation duration period; - As the above, but with separate modeling of probability distribution for the middle and high probability quantiles. - Method is similar to the first one, but with a threshold of 0,36 mm/min of intensity; - Another method proposed by the Russian hydrologist G. A. Aleksiev for regionalization of estimates over some territory, improved and adapted by S. Gerasimov for Bulgaria; - Next method is considering only

Probability density function modeling of scalar mixing from concentrated sources in turbulent channel flow

OpenAIRE

Bakosi, J.; Franzese, P.; Boybeyi, Z.

2010-01-01

Dispersion of a passive scalar from concentrated sources in fully developed turbulent channel flow is studied with the probability density function (PDF) method. The joint PDF of velocity, turbulent frequency and scalar concentration is represented by a large number of Lagrangian particles. A stochastic near-wall PDF model combines the generalized Langevin model of Haworth & Pope with Durbin's method of elliptic relaxation to provide a mathematically exact treatment of convective and viscous ...

How to model a negligible probability under the WTO sanitary and phytosanitary agreement?

Science.gov (United States)

Powell, Mark R

2013-06-01

Since the 1997 EC--Hormones decision, World Trade Organization (WTO) Dispute Settlement Panels have wrestled with the question of what constitutes a negligible risk under the Sanitary and Phytosanitary Agreement. More recently, the 2010 WTO Australia--Apples Panel focused considerable attention on the appropriate quantitative model for a negligible probability in a risk assessment. The 2006 Australian Import Risk Analysis for Apples from New Zealand translated narrative probability statements into quantitative ranges. The uncertainty about a "negligible" probability was characterized as a uniform distribution with a minimum value of zero and a maximum value of 10(-6) . The Australia - Apples Panel found that the use of this distribution would tend to overestimate the likelihood of "negligible" events and indicated that a triangular distribution with a most probable value of zero and a maximum value of 10⁻⁶ would correct the bias. The Panel observed that the midpoint of the uniform distribution is 5 × 10⁻⁷ but did not consider that the triangular distribution has an expected value of 3.3 × 10⁻⁷. Therefore, if this triangular distribution is the appropriate correction, the magnitude of the bias found by the Panel appears modest. The Panel's detailed critique of the Australian risk assessment, and the conclusions of the WTO Appellate Body about the materiality of flaws found by the Panel, may have important implications for the standard of review for risk assessments under the WTO SPS Agreement. © 2012 Society for Risk Analysis.

Multivariate modeling of complications with data driven variable selection: Guarding against overfitting and effects of data set size

International Nuclear Information System (INIS)

Schaaf, Arjen van der; Xu Chengjian; Luijk, Peter van; Veld, Aart A. van’t; Langendijk, Johannes A.; Schilstra, Cornelis

2012-01-01

Purpose: Multivariate modeling of complications after radiotherapy is frequently used in conjunction with data driven variable selection. This study quantifies the risk of overfitting in a data driven modeling method using bootstrapping for data with typical clinical characteristics, and estimates the minimum amount of data needed to obtain models with relatively high predictive power. Materials and methods: To facilitate repeated modeling and cross-validation with independent datasets for the assessment of true predictive power, a method was developed to generate simulated data with statistical properties similar to real clinical data sets. Characteristics of three clinical data sets from radiotherapy treatment of head and neck cancer patients were used to simulate data with set sizes between 50 and 1000 patients. A logistic regression method using bootstrapping and forward variable selection was used for complication modeling, resulting for each simulated data set in a selected number of variables and an estimated predictive power. The true optimal number of variables and true predictive power were calculated using cross-validation with very large independent data sets. Results: For all simulated data set sizes the number of variables selected by the bootstrapping method was on average close to the true optimal number of variables, but showed considerable spread. Bootstrapping is more accurate in selecting the optimal number of variables than the AIC and BIC alternatives, but this did not translate into a significant difference of the true predictive power. The true predictive power asymptotically converged toward a maximum predictive power for large data sets, and the estimated predictive power converged toward the true predictive power. More than half of the potential predictive power is gained after approximately 200 samples. Our simulations demonstrated severe overfitting (a predicative power lower than that of predicting 50% probability) in a number of small

Intraoperative and early postoperative complications of manual sutureless cataract extraction.

Science.gov (United States)

Iqbal, Yasir; Zia, Sohail; Baig Mirza, Aneeq Ullah

2014-04-01

To determine the intraoperative and early postoperative complications of manual sutureless cataract extraction. Case series. Redo Eye Hospital, Rawalpindi, Pakistan, from January 2009 to December 2010. Three hundred patients of cataract through purposive non-probability sampling were selected. The patients underwent manual sutureless cataract surgery (MSCS) by single experienced surgeon and intraoperative complications were documented. The surgical technique was modified to deal with any intraoperative complications accordingly. Patients were examined on the first postoperative day and on the first postoperative week for any postoperative complications. The data was entered in Statistical Package for Social Sciences (SPSS) version 13.0 and the results were calculated in frequencies. Among the 300 cases, 81.3% surgeries went uneventful whereas 18.6% had some complication. The common intraoperative complications were superior button-hole formation in 5%; posterior capsular rent in 5% and premature entry with iris prolapse in 3% cases. Postoperatively, the commonly encountered complications were striate keratopathy in 9.6% and hyphema 9%. At first week follow-up, 4% had striate keratopathy and 0.6% had hyphema. Striate keratopathy resolved with topical medication on subsequent follow-up. A total of 9 cases (3%) underwent second surgery: 2 cases for lens matter wash, 2 cases for hyphema and 5 cases needed suturing of wound for shallow anterior chamber due to wound leak. Superior button-hole formation, posterior capsular rent and premature entry were the common intraoperative complications of MSCS whereas the common early postoperative complications were striate keratopathy and hyphema.

Factors influencing reporting and harvest probabilities in North American geese

Science.gov (United States)

Zimmerman, G.S.; Moser, T.J.; Kendall, W.L.; Doherty, P.F.; White, Gary C.; Caswell, D.F.

2009-01-01

We assessed variation in reporting probabilities of standard bands among species, populations, harvest locations, and size classes of North American geese to enable estimation of unbiased harvest probabilities. We included reward (US10,20,30,50, or100) and control (0) banded geese from 16 recognized goose populations of 4 species: Canada (Branta canadensis), cackling (B. hutchinsii), Ross's (Chen rossii), and snow geese (C. caerulescens). We incorporated spatially explicit direct recoveries and live recaptures into a multinomial model to estimate reporting, harvest, and band-retention probabilities. We compared various models for estimating harvest probabilities at country (United States vs. Canada), flyway (5 administrative regions), and harvest area (i.e., flyways divided into northern and southern sections) scales. Mean reporting probability of standard bands was 0.73 (95 CI 0.690.77). Point estimates of reporting probabilities for goose populations or spatial units varied from 0.52 to 0.93, but confidence intervals for individual estimates overlapped and model selection indicated that models with species, population, or spatial effects were less parsimonious than those without these effects. Our estimates were similar to recently reported estimates for mallards (Anas platyrhynchos). We provide current harvest probability estimates for these populations using our direct measures of reporting probability, improving the accuracy of previous estimates obtained from recovery probabilities alone. Goose managers and researchers throughout North America can use our reporting probabilities to correct recovery probabilities estimated from standard banding operations for deriving spatially explicit harvest probabilities.

Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows

Science.gov (United States)

Haberlandt, U.; Radtke, I.

2014-01-01

Derived flood frequency analysis allows the estimation of design floods with hydrological modeling for poorly observed basins considering change and taking into account flood protection measures. There are several possible choices regarding precipitation input, discharge output and consequently the calibration of the model. The objective of this study is to compare different calibration strategies for a hydrological model considering various types of rainfall input and runoff output data sets and to propose the most suitable approach. Event based and continuous, observed hourly rainfall data as well as disaggregated daily rainfall and stochastically generated hourly rainfall data are used as input for the model. As output, short hourly and longer daily continuous flow time series as well as probability distributions of annual maximum peak flow series are employed. The performance of the strategies is evaluated using the obtained different model parameter sets for continuous simulation of discharge in an independent validation period and by comparing the model derived flood frequency distributions with the observed one. The investigations are carried out for three mesoscale catchments in northern Germany with the hydrological model HEC-HMS (Hydrologic Engineering Center's Hydrologic Modeling System). The results show that (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated using a small sample of extreme values works quite well for the simulation of continuous time series with moderate length but not vice versa, and (III) the best performance with small uncertainty is obtained when stochastic precipitation data and the observed probability distribution of peak flows are used for model calibration. This outcome suggests to calibrate a hydrological model directly on probability distributions of observed peak flows using stochastic rainfall as input if its purpose is the

The creation and evaluation of a model predicting the probability of conception in seasonal-calving, pasture-based dairy cows.

Science.gov (United States)

Fenlon, Caroline; O'Grady, Luke; Doherty, Michael L; Dunnion, John; Shalloo, Laurence; Butler, Stephen T

2017-07-01

Reproductive performance in pasture-based production systems has a fundamentally important effect on economic efficiency. The individual factors affecting the probability of submission and conception are multifaceted and have been extensively researched. The present study analyzed some of these factors in relation to service-level probability of conception in seasonal-calving pasture-based dairy cows to develop a predictive model of conception. Data relating to 2,966 services from 737 cows on 2 research farms were used for model development and data from 9 commercial dairy farms were used for model testing, comprising 4,212 services from 1,471 cows. The data spanned a 15-yr period and originated from seasonal-calving pasture-based dairy herds in Ireland. The calving season for the study herds extended from January to June, with peak calving in February and March. A base mixed-effects logistic regression model was created using a stepwise model-building strategy and incorporated parity, days in milk, interservice interval, calving difficulty, and predicted transmitting abilities for calving interval and milk production traits. To attempt to further improve the predictive capability of the model, the addition of effects that were not statistically significant was considered, resulting in a final model composed of the base model with the inclusion of BCS at service. The models' predictions were evaluated using discrimination to measure their ability to correctly classify positive and negative cases. Precision, recall, F-score, and area under the receiver operating characteristic curve (AUC) were calculated. Calibration tests measured the accuracy of the predicted probabilities. These included tests of overall goodness-of-fit, bias, and calibration error. Both models performed better than using the population average probability of conception. Neither of the models showed high levels of discrimination (base model AUC 0.61, final model AUC 0.62), possibly because of the

Multivariate quantile mapping bias correction: an N-dimensional probability density function transform for climate model simulations of multiple variables

Science.gov (United States)

Cannon, Alex J.

2018-01-01

Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin

Mathematical models of tumor growth: translating absorbed dose to tumor control probability

International Nuclear Information System (INIS)

Sgouros, G.

1996-01-01

cell loss due to irradiation, the log-kill model, therefore, predicts that incomplete treatment of a kinetically heterogeneous tumor will yield a more proliferative tumor. The probability of tumor control in such a simulation may be obtained from the nadir in tumor cell number. If the nadir is not sufficiently low to yield a high probability of tumor control, then the tumor will re-grow. Since tumors in each sub-population are assumed lost at the same rate, cells comprising the sub-population with the shortest potential doubling time will re-grow the fastest, yielding a recurrent tumor that is more proliferative. A number of assumptions and simplifications are both implicitly and explicitly made in converting absorbed dose to tumor control probability. The modeling analyses described above must, therefore, be viewed in terms of understanding and evaluating different treatment approaches with the goal of treatment optimization rather than outcome prediction

Probability Weighting and Loss Aversion in Futures Hedging

NARCIS (Netherlands)

Mattos, F.; Garcia, P.; Pennings, J.M.E.

2008-01-01

We analyze how the introduction of probability weighting and loss aversion in a futures hedging model affects decision making. Analytical findings indicate that probability weighting alone always affects optimal hedge ratios, while loss and risk aversion only have an impact when probability

Probability for Weather and Climate

Science.gov (United States)

Smith, L. A.

2013-12-01

Over the last 60 years, the availability of large-scale electronic computers has stimulated rapid and significant advances both in meteorology and in our understanding of the Earth System as a whole. The speed of these advances was due, in large part, to the sudden ability to explore nonlinear systems of equations. The computer allows the meteorologist to carry a physical argument to its conclusion; the time scales of weather phenomena then allow the refinement of physical theory, numerical approximation or both in light of new observations. Prior to this extension, as Charney noted, the practicing meteorologist could ignore the results of theory with good conscience. Today, neither the practicing meteorologist nor the practicing climatologist can do so, but to what extent, and in what contexts, should they place the insights of theory above quantitative simulation? And in what circumstances can one confidently estimate the probability of events in the world from model-based simulations? Despite solid advances of theory and insight made possible by the computer, the fidelity of our models of climate differs in kind from the fidelity of models of weather. While all prediction is extrapolation in time, weather resembles interpolation in state space, while climate change is fundamentally an extrapolation. The trichotomy of simulation, observation and theory which has proven essential in meteorology will remain incomplete in climate science. Operationally, the roles of probability, indeed the kinds of probability one has access too, are different in operational weather forecasting and climate services. Significant barriers to forming probability forecasts (which can be used rationally as probabilities) are identified. Monte Carlo ensembles can explore sensitivity, diversity, and (sometimes) the likely impact of measurement uncertainty and structural model error. The aims of different ensemble strategies, and fundamental differences in ensemble design to support of

Quantum probability and cognitive modeling: some cautions and a promising direction in modeling physics learning.

Science.gov (United States)

Franceschetti, Donald R; Gire, Elizabeth

2013-06-01

Quantum probability theory offers a viable alternative to classical probability, although there are some ambiguities inherent in transferring the quantum formalism to a less determined realm. A number of physicists are now looking at the applicability of quantum ideas to the assessment of physics learning, an area particularly suited to quantum probability ideas.

Probability of bystander effect induced by alpha-particles emitted by radon progeny using the analytical model of tracheobronchial tree

International Nuclear Information System (INIS)

Jovanovic, B.; Nikezic, D.

2010-01-01

Radiation-induced biological bystander effects have become a phenomenon associated with the interaction of radiation with cells. There is a need to include the influence of biological effects in the dosimetry of the human lung. With this aim, the purpose of this work is to calculate the probability of bystander effect induced by alpha-particle radiation on sensitive cells of the human lung. Probability was calculated by applying the analytical model cylinder bifurcation, which was created to simulate the geometry of the human lung with the geometric distribution of cell nuclei in the airway wall of the tracheobronchial tree. This analytical model of the human tracheobronchial tree represents the extension of the ICRP 66 model, and follows it as much as possible. Reported probabilities are calculated for various targets and alpha-particle energies. Probability of bystander effect has been calculated for alpha particles with 6 and 7.69 MeV energies, which are emitted in the 222 Rn chain. The application of these results may enhance current dose risk estimation approaches in the sense of the inclusion of the influence of the biological effects. (authors)

Concepts of probability theory

CERN Document Server

Pfeiffer, Paul E

1979-01-01

Using the Kolmogorov model, this intermediate-level text discusses random variables, probability distributions, mathematical expectation, random processes, more. For advanced undergraduates students of science, engineering, or math. Includes problems with answers and six appendixes. 1965 edition.

Robust estimation of the expected survival probabilities from high-dimensional Cox models with biomarker-by-treatment interactions in randomized clinical trials

Directory of Open Access Journals (Sweden)

Nils Ternès

2017-05-01

Full Text Available Abstract Background Thanks to the advances in genomics and targeted treatments, more and more prediction models based on biomarkers are being developed to predict potential benefit from treatments in a randomized clinical trial. Despite the methodological framework for the development and validation of prediction models in a high-dimensional setting is getting more and more established, no clear guidance exists yet on how to estimate expected survival probabilities in a penalized model with biomarker-by-treatment interactions. Methods Based on a parsimonious biomarker selection in a penalized high-dimensional Cox model (lasso or adaptive lasso, we propose a unified framework to: estimate internally the predictive accuracy metrics of the developed model (using double cross-validation; estimate the individual survival probabilities at a given timepoint; construct confidence intervals thereof (analytical or bootstrap; and visualize them graphically (pointwise or smoothed with spline. We compared these strategies through a simulation study covering scenarios with or without biomarker effects. We applied the strategies to a large randomized phase III clinical trial that evaluated the effect of adding trastuzumab to chemotherapy in 1574 early breast cancer patients, for which the expression of 462 genes was measured. Results In our simulations, penalized regression models using the adaptive lasso estimated the survival probability of new patients with low bias and standard error; bootstrapped confidence intervals had empirical coverage probability close to the nominal level across very different scenarios. The double cross-validation performed on the training data set closely mimicked the predictive accuracy of the selected models in external validation data. We also propose a useful visual representation of the expected survival probabilities using splines. In the breast cancer trial, the adaptive lasso penalty selected a prediction model with 4

Renal posttransplant's vascular complications

Directory of Open Access Journals (Sweden)

Bašić Dragoslav

2003-01-01

Full Text Available INTRODUCTION Despite high graft and recipient survival figures worldwide today, a variety of technical complications can threaten the transplant in the postoperative period. Vascular complications are commonly related to technical problems in establishing vascular continuity or to damage that occurs during donor nephrectomy or preservation [13]. AIM The aim of the presenting study is to evaluate counts and rates of vascular complications after renal transplantation and to compare the outcome by donor type. MATERIAL AND METHODS A total of 463 kidneys (319 from living related donor LD and 144 from cadaveric donor - CD were transplanted during the period between June 1975 and December 1998 at the Urology & Nephrology Institute of Clinical Centre of Serbia in Belgrade. Average recipients' age was 33.7 years (15-54 in LD group and 39.8 (19-62 in CD group. Retrospectively, we analyzed medical records of all recipients. Statistical analysis is estimated using Hi-squared test and Fischer's test of exact probability. RESULTS Major vascular complications including vascular anastomosis thrombosis, internal iliac artery stenosis, internal iliac artery rupture obliterant vasculitis and external iliac vein rupture were analyzed. In 25 recipients (5.4% some of major vascular complications were detected. Among these cases, 22 of them were from CD group vs. three from LD group. Relative rate of these complications was higher in CD group vs. LD group (p<0.0001. Among these complications dominant one was vascular anastomosis thrombosis which occurred in 18 recipients (17 from CD vs. one from LD. Of these recipients 16 from CD lost the graft, while the rest of two (one from each group had lethal outcome. DISCUSSION Thrombosis of renal allograft vascular anastomosis site is the most severe complication following renal transplantation. In the literature, renal allograft thrombosis is reported with different incidence rates, from 0.5-4% [14, 15, 16]. Data from the

Swedish earthquakes and acceleration probabilities

International Nuclear Information System (INIS)

Slunga, R.

1979-03-01

A method to assign probabilities to ground accelerations for Swedish sites is described. As hardly any nearfield instrumental data is available we are left with the problem of interpreting macroseismic data in terms of acceleration. By theoretical wave propagation computations the relation between seismic strength of the earthquake, focal depth, distance and ground accelerations are calculated. We found that most Swedish earthquake of the area, the 1904 earthquake 100 km south of Oslo, is an exception and probably had a focal depth exceeding 25 km. For the nuclear power plant sites an annual probability of 10 -5 has been proposed as interesting. This probability gives ground accelerations in the range 5-20 % for the sites. This acceleration is for a free bedrock site. For consistency all acceleration results in this study are given for bedrock sites. When applicating our model to the 1904 earthquake and assuming the focal zone to be in the lower crust we get the epicentral acceleration of this earthquake to be 5-15 % g. The results above are based on an analyses of macrosismic data as relevant instrumental data is lacking. However, the macroseismic acceleration model deduced in this study gives epicentral ground acceleration of small Swedish earthquakes in agreement with existent distant instrumental data. (author)

A statistical model for deriving probability distributions of contamination for accidental releases

International Nuclear Information System (INIS)

ApSimon, H.M.; Davison, A.C.

1986-01-01

Results generated from a detailed long-range transport model, MESOS, simulating dispersal of a large number of hypothetical releases of radionuclides in a variety of meteorological situations over Western Europe have been used to derive a simpler statistical model, MESOSTAT. This model may be used to generate probability distributions of different levels of contamination at a receptor point 100-1000 km or so from the source (for example, across a frontier in another country) without considering individual release and dispersal scenarios. The model is embodied in a series of equations involving parameters which are determined from such factors as distance between source and receptor, nuclide decay and deposition characteristics, release duration, and geostrophic windrose at the source. Suitable geostrophic windrose data have been derived for source locations covering Western Europe. Special attention has been paid to the relatively improbable extreme values of contamination at the top end of the distribution. The MESOSTAT model and its development are described, with illustrations of its use and comparison with the original more detailed modelling techniques. (author)

Current recommendations on the estimation of transition probabilities in Markov cohort models for use in health care decision-making: a targeted literature review

Directory of Open Access Journals (Sweden)

Olariu E

2017-09-01

Full Text Available Elena Olariu,1 Kevin K Cadwell,1 Elizabeth Hancock,1 David Trueman,1 Helene Chevrou-Severac2 1PHMR Ltd, London, UK; 2Takeda Pharmaceuticals International AG, Zurich, Switzerland Objective: Although Markov cohort models represent one of the most common forms of decision-analytic models used in health care decision-making, correct implementation of such models requires reliable estimation of transition probabilities. This study sought to identify consensus statements or guidelines that detail how such transition probability matrices should be estimated. Methods: A literature review was performed to identify relevant publications in the following databases: Medline, Embase, the Cochrane Library, and PubMed. Electronic searches were supplemented by manual-searches of health technology assessment (HTA websites in Australia, Belgium, Canada, France, Germany, Ireland, Norway, Portugal, Sweden, and the UK. One reviewer assessed studies for eligibility. Results: Of the 1,931 citations identified in the electronic searches, no studies met the inclusion criteria for full-text review, and no guidelines on transition probabilities in Markov models were identified. Manual-searching of the websites of HTA agencies identified ten guidelines on economic evaluations (Australia, Belgium, Canada, France, Germany, Ireland, Norway, Portugal, Sweden, and UK. All identified guidelines provided general guidance on how to develop economic models, but none provided guidance on the calculation of transition probabilities. One relevant publication was identified following review of the reference lists of HTA agency guidelines: the International Society for Pharmacoeconomics and Outcomes Research taskforce guidance. This provided limited guidance on the use of rates and probabilities. Conclusions: There is limited formal guidance available on the estimation of transition probabilities for use in decision-analytic models. Given the increasing importance of cost

A new formulation of the probability density function in random walk models for atmospheric dispersion

DEFF Research Database (Denmark)

Falk, Anne Katrine Vinther; Gryning, Sven-Erik

1997-01-01

In this model for atmospheric dispersion particles are simulated by the Langevin Equation, which is a stochastic differential equation. It uses the probability density function (PDF) of the vertical velocity fluctuations as input. The PDF is constructed as an expansion after Hermite polynomials...

A Quantum Theoretical Explanation for Probability Judgment Errors

Science.gov (United States)

Busemeyer, Jerome R.; Pothos, Emmanuel M.; Franco, Riccardo; Trueblood, Jennifer S.

2011-01-01

A quantum probability model is introduced and used to explain human probability judgment errors including the conjunction and disjunction fallacies, averaging effects, unpacking effects, and order effects on inference. On the one hand, quantum theory is similar to other categorization and memory models of cognition in that it relies on vector…

Impact of Age on the Risk of Advanced Colorectal Neoplasia in a Young Population: An Analysis Using the Predicted Probability Model.

Science.gov (United States)

Jung, Yoon Suk; Park, Chan Hyuk; Kim, Nam Hee; Lee, Mi Yeon; Park, Dong Il

2017-09-01

The incidence of colorectal cancer is decreasing in adults aged ≥50 years and increasing in those aged probability models for ACRN in a population aged 30-49 years. Of 96,235 participants, 57,635 and 38,600 were included in the derivation and validation cohorts, respectively. The predicted probability model considered age, sex, body mass index, family history of colorectal cancer, and smoking habits, as follows: Y ACRN  = -8.755 + 0.080·X age  - 0.055·X male  + 0.041·X BMI  + 0.200·X family_history_of_CRC  + 0.218·X former_smoker  + 0.644·X current_smoker . The optimal cutoff value for the predicted probability of ACRN by Youden index was 1.14%. The area under the receiver-operating characteristic curve (AUROC) values of our model for ACRN were higher than those of the previously established Asia-Pacific Colorectal Screening (APCS), Korean Colorectal Screening (KCS), and Kaminski's scoring models [AUROC (95% confidence interval): model in the current study, 0.673 (0.648-0.697); vs. APCS, 0.588 (0.564-0.611), P probability model can assess the risk of ACRN more accurately than existing models, including the APCS, KCS, and Kaminski's scoring models.

Linear positivity and virtual probability

International Nuclear Information System (INIS)

Hartle, James B.

2004-01-01

We investigate the quantum theory of closed systems based on the linear positivity decoherence condition of Goldstein and Page. The objective of any quantum theory of a closed system, most generally the universe, is the prediction of probabilities for the individual members of sets of alternative coarse-grained histories of the system. Quantum interference between members of a set of alternative histories is an obstacle to assigning probabilities that are consistent with the rules of probability theory. A quantum theory of closed systems therefore requires two elements: (1) a condition specifying which sets of histories may be assigned probabilities and (2) a rule for those probabilities. The linear positivity condition of Goldstein and Page is the weakest of the general conditions proposed so far. Its general properties relating to exact probability sum rules, time neutrality, and conservation laws are explored. Its inconsistency with the usual notion of independent subsystems in quantum mechanics is reviewed. Its relation to the stronger condition of medium decoherence necessary for classicality is discussed. The linear positivity of histories in a number of simple model systems is investigated with the aim of exhibiting linearly positive sets of histories that are not decoherent. The utility of extending the notion of probability to include values outside the range of 0-1 is described. Alternatives with such virtual probabilities cannot be measured or recorded, but can be used in the intermediate steps of calculations of real probabilities. Extended probabilities give a simple and general way of formulating quantum theory. The various decoherence conditions are compared in terms of their utility for characterizing classicality and the role they might play in further generalizations of quantum mechanics

Application of a weighted spatial probability model in GIS to analyse landslides in Penang Island, Malaysia

Directory of Open Access Journals (Sweden)

Samy Ismail Elmahdy

2016-01-01

Full Text Available In the current study, Penang Island, which is one of the several mountainous areas in Malaysia that is often subjected to landslide hazard, was chosen for further investigation. A multi-criteria Evaluation and the spatial probability weighted approach and model builder was applied to map and analyse landslides in Penang Island. A set of automated algorithms was used to construct new essential geological and morphometric thematic maps from remote sensing data. The maps were ranked using the weighted probability spatial model based on their contribution to the landslide hazard. Results obtained showed that sites at an elevation of 100–300 m, with steep slopes of 10°–37° and slope direction (aspect in the E and SE directions were areas of very high and high probability for the landslide occurrence; the total areas were 21.393 km2 (11.84% and 58.690 km2 (32.48%, respectively. The obtained map was verified by comparing variogram models of the mapped and the occurred landslide locations and showed a strong correlation with the locations of occurred landslides, indicating that the proposed method can successfully predict the unpredictable landslide hazard. The method is time and cost effective and can be used as a reference for geological and geotechnical engineers.

Joint probabilities and quantum cognition

International Nuclear Information System (INIS)

Acacio de Barros, J.

2012-01-01

In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

Joint probabilities and quantum cognition

Energy Technology Data Exchange (ETDEWEB)

Acacio de Barros, J. [Liberal Studies, 1600 Holloway Ave., San Francisco State University, San Francisco, CA 94132 (United States)

2012-12-18

In this paper we discuss the existence of joint probability distributions for quantumlike response computations in the brain. We do so by focusing on a contextual neural-oscillator model shown to reproduce the main features of behavioral stimulus-response theory. We then exhibit a simple example of contextual random variables not having a joint probability distribution, and describe how such variables can be obtained from neural oscillators, but not from a quantum observable algebra.

Inferring Pairwise Interactions from Biological Data Using Maximum-Entropy Probability Models.

Directory of Open Access Journals (Sweden)

Richard R Stein

2015-07-01

Full Text Available Maximum entropy-based inference methods have been successfully used to infer direct interactions from biological datasets such as gene expression data or sequence ensembles. Here, we review undirected pairwise maximum-entropy probability models in two categories of data types, those with continuous and categorical random variables. As a concrete example, we present recently developed inference methods from the field of protein contact prediction and show that a basic set of assumptions leads to similar solution strategies for inferring the model parameters in both variable types. These parameters reflect interactive couplings between observables, which can be used to predict global properties of the biological system. Such methods are applicable to the important problems of protein 3-D structure prediction and association of gene-gene networks, and they enable potential applications to the analysis of gene alteration patterns and to protein design.

Probability

CERN Document Server

Shiryaev, A N

1996-01-01

This book contains a systematic treatment of probability from the ground up, starting with intuitive ideas and gradually developing more sophisticated subjects, such as random walks, martingales, Markov chains, ergodic theory, weak convergence of probability measures, stationary stochastic processes, and the Kalman-Bucy filter Many examples are discussed in detail, and there are a large number of exercises The book is accessible to advanced undergraduates and can be used as a text for self-study This new edition contains substantial revisions and updated references The reader will find a deeper study of topics such as the distance between probability measures, metrization of weak convergence, and contiguity of probability measures Proofs for a number of some important results which were merely stated in the first edition have been added The author included new material on the probability of large deviations, and on the central limit theorem for sums of dependent random variables

Development of a methodology for probable maximum precipitation estimation over the American River watershed using the WRF model

Science.gov (United States)

Tan, Elcin

A new physically-based methodology for probable maximum precipitation (PMP) estimation is developed over the American River Watershed (ARW) using the Weather Research and Forecast (WRF-ARW) model. A persistent moisture flux convergence pattern, called Pineapple Express, is analyzed for 42 historical extreme precipitation events, and it is found that Pineapple Express causes extreme precipitation over the basin of interest. An average correlation between moisture flux convergence and maximum precipitation is estimated as 0.71 for 42 events. The performance of the WRF model is verified for precipitation by means of calibration and independent validation of the model. The calibration procedure is performed only for the first ranked flood event 1997 case, whereas the WRF model is validated for 42 historical cases. Three nested model domains are set up with horizontal resolutions of 27 km, 9 km, and 3 km over the basin of interest. As a result of Chi-square goodness-of-fit tests, the hypothesis that "the WRF model can be used in the determination of PMP over the ARW for both areal average and point estimates" is accepted at the 5% level of significance. The sensitivities of model physics options on precipitation are determined using 28 microphysics, atmospheric boundary layer, and cumulus parameterization schemes combinations. It is concluded that the best triplet option is Thompson microphysics, Grell 3D ensemble cumulus, and YSU boundary layer (TGY), based on 42 historical cases, and this TGY triplet is used for all analyses of this research. Four techniques are proposed to evaluate physically possible maximum precipitation using the WRF: 1. Perturbations of atmospheric conditions; 2. Shift in atmospheric conditions; 3. Replacement of atmospheric conditions among historical events; and 4. Thermodynamically possible worst-case scenario creation. Moreover, climate change effect on precipitation is discussed by emphasizing temperature increase in order to determine the

Intraoperative and Early Postoperative Complications of Manual Sutureless Cataract Extraction

International Nuclear Information System (INIS)

Iqbal, Y.; Zia, S.; Mirza, A. B.

2014-01-01

Objective: To determine the intraoperative and early postoperative complications of manual sutureless cataract extraction. Study Design: Case series. Place and Duration of Study: Redo Eye Hospital, Rawalpindi, Pakistan, from January 2009 to December 2010. Methodology: Three hundred patients of cataract through purposive non-probability sampling were selected. The patients underwent manual sutureless cataract surgery (MSCS) by single experienced surgeon and intraoperative complications were documented. The surgical technique was modified to deal with any intraoperative complications accordingly. Patients were examined on the first postoperative day and on the first postoperative week for any postoperative complications. The data was entered in Statistical Package for Social Sciences (SPSS) version 13.0 and the results were calculated in frequencies. Results: Among the 300 cases, 81.3% surgeries went uneventful whereas 18.6% had some complication. The common intraoperative complications were superior button-hole formation in 5%; posterior capsular rent in 5% and premature entry with iris prolapse in 3% cases. Postoperatively, the commonly encountered complications were striate keratopathy in 9.6% and hyphema 9%. At first week follow-up, 4% had striate keratopathy and 0.6% had hyphema. Striate keratopathy resolved with topical medication on subsequent follow-up. A total of 9 cases (3%) underwent second surgery: 2 cases for lens matter wash, 2 cases for hyphema and 5 cases needed suturing of wound for shallow anterior chamber due to wound leak. Conclusion: Superior button-hole formation, posterior capsular rent and premature entry were the common intraoperative complications of MSCS whereas the common early postoperative complications were striate keratopathy and hyphema. (author)

A new way of thinking about complications of prematurity.

Science.gov (United States)

Moore, Tiffany A; Berger, Ann M; Wilson, Margaret E

2014-01-01

The morbidity and mortality of preterm infants are impacted by their ability to maintain physiologic homeostasis using metabolic, endocrine, and immunologic mechanisms independent of the mother's placenta. Exploring McEwen's allostatic load model in preterm infants provides a new way to understand the altered physiologic processes associated with frequently occurring complications of prematurity such as bronchopulmonary dysplasia, intraventricular hemorrhage, necrotizing enterocolitis, and retinopathy of prematurity. The purpose of this article is to present a new model to enhance understanding of the altered physiologic processes associated with complications of prematurity. The model of allostatic load and complications of prematurity was derived to explore the relationship between general stress of prematurity and complications of prematurity. The proposed model uses the concepts of general stress of prematurity, allostasis, physiologic response patterns (adaptive-maladaptive), allostatic load, and complications of prematurity. These concepts are defined and theoretical relationships in the proposed model are interpreted using the four maladaptive response patterns of repeated hits, lack of adaptation, prolonged response, and inadequate response. Empirical evidence for cortisol, inflammation, and oxidative stress responses are used to support the theoretical relationships. The proposed model provides a new way of thinking about physiologic dysregulation in preterm infants. The ability to describe and understand complex physiologic mechanisms involved in complications of prematurity is essential for research. Advancing the knowledge of complications of prematurity will advance clinical practice and research and lead to testing of interventions to reduce negative outcomes in preterm infants.

Modeling tumor control probability for spatially inhomogeneous risk of failure based on clinical outcome data

DEFF Research Database (Denmark)

Lühr, Armin; Löck, Steffen; Jakobi, Annika

2017-01-01

PURPOSE: Objectives of this work are (1) to derive a general clinically relevant approach to model tumor control probability (TCP) for spatially variable risk of failure and (2) to demonstrate its applicability by estimating TCP for patients planned for photon and proton irradiation. METHODS AND ...

PHOTOMETRIC REDSHIFTS AND QUASAR PROBABILITIES FROM A SINGLE, DATA-DRIVEN GENERATIVE MODEL

International Nuclear Information System (INIS)

Bovy, Jo; Hogg, David W.; Weaver, Benjamin A.; Myers, Adam D.; Hennawi, Joseph F.; McMahon, Richard G.; Schiminovich, David; Sheldon, Erin S.; Brinkmann, Jon; Schneider, Donald P.

2012-01-01

We describe a technique for simultaneously classifying and estimating the redshift of quasars. It can separate quasars from stars in arbitrary redshift ranges, estimate full posterior distribution functions for the redshift, and naturally incorporate flux uncertainties, missing data, and multi-wavelength photometry. We build models of quasars in flux-redshift space by applying the extreme deconvolution technique to estimate the underlying density. By integrating this density over redshift, one can obtain quasar flux densities in different redshift ranges. This approach allows for efficient, consistent, and fast classification and photometric redshift estimation. This is achieved by combining the speed obtained by choosing simple analytical forms as the basis of our density model with the flexibility of non-parametric models through the use of many simple components with many parameters. We show that this technique is competitive with the best photometric quasar classification techniques—which are limited to fixed, broad redshift ranges and high signal-to-noise ratio data—and with the best photometric redshift techniques when applied to broadband optical data. We demonstrate that the inclusion of UV and NIR data significantly improves photometric quasar-star separation and essentially resolves all of the redshift degeneracies for quasars inherent to the ugriz filter system, even when included data have a low signal-to-noise ratio. For quasars spectroscopically confirmed by the SDSS 84% and 97% of the objects with Galaxy Evolution Explorer UV and UKIDSS NIR data have photometric redshifts within 0.1 and 0.3, respectively, of the spectroscopic redshift; this amounts to about a factor of three improvement over ugriz-only photometric redshifts. Our code to calculate quasar probabilities and redshift probability distributions is publicly available.

Subjective Probabilities for State-Dependent Continuous Utility

NARCIS (Netherlands)

P.P. Wakker (Peter)

1987-01-01

textabstractFor the expected utility model with state dependent utilities, Karni, Schmeidler and Vind (1983) have shown how to recover uniquely the involved subjective probabilities if the preferences, contingent on a hypothetical probability distribution over the state space, are known. This they

Contributions to quantum probability

International Nuclear Information System (INIS)

Fritz, Tobias

2010-01-01

Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a finite set can occur as the outcome

Electrofishing capture probability of smallmouth bass in streams

Science.gov (United States)

Dauwalter, D.C.; Fisher, W.L.

2007-01-01

Abundance estimation is an integral part of understanding the ecology and advancing the management of fish populations and communities. Mark-recapture and removal methods are commonly used to estimate the abundance of stream fishes. Alternatively, abundance can be estimated by dividing the number of individuals sampled by the probability of capture. We conducted a mark-recapture study and used multiple repeated-measures logistic regression to determine the influence of fish size, sampling procedures, and stream habitat variables on the cumulative capture probability for smallmouth bass Micropterus dolomieu in two eastern Oklahoma streams. The predicted capture probability was used to adjust the number of individuals sampled to obtain abundance estimates. The observed capture probabilities were higher for larger fish and decreased with successive electrofishing passes for larger fish only. Model selection suggested that the number of electrofishing passes, fish length, and mean thalweg depth affected capture probabilities the most; there was little evidence for any effect of electrofishing power density and woody debris density on capture probability. Leave-one-out cross validation showed that the cumulative capture probability model predicts smallmouth abundance accurately. ?? Copyright by the American Fisheries Society 2007.

Nonparametric estimation of transition probabilities in the non-Markov illness-death model: A comparative study.

Science.gov (United States)

de Uña-Álvarez, Jacobo; Meira-Machado, Luís

2015-06-01

Multi-state models are often used for modeling complex event history data. In these models the estimation of the transition probabilities is of particular interest, since they allow for long-term predictions of the process. These quantities have been traditionally estimated by the Aalen-Johansen estimator, which is consistent if the process is Markov. Several non-Markov estimators have been proposed in the recent literature, and their superiority with respect to the Aalen-Johansen estimator has been proved in situations in which the Markov condition is strongly violated. However, the existing estimators have the drawback of requiring that the support of the censoring distribution contains the support of the lifetime distribution, which is not often the case. In this article, we propose two new methods for estimating the transition probabilities in the progressive illness-death model. Some asymptotic results are derived. The proposed estimators are consistent regardless the Markov condition and the referred assumption about the censoring support. We explore the finite sample behavior of the estimators through simulations. The main conclusion of this piece of research is that the proposed estimators are much more efficient than the existing non-Markov estimators in most cases. An application to a clinical trial on colon cancer is included. Extensions to progressive processes beyond the three-state illness-death model are discussed. © 2015, The International Biometric Society.

A hydroclimatological approach to predicting regional landslide probability using Landlab

Directory of Open Access Journals (Sweden)

R. Strauch

2018-02-01

Full Text Available We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m, and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

A hydroclimatological approach to predicting regional landslide probability using Landlab

Science.gov (United States)

Strauch, Ronda; Istanbulluoglu, Erkan; Nudurupati, Sai Siddhartha; Bandaragoda, Christina; Gasparini, Nicole M.; Tucker, Gregory E.

2018-02-01

We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

Fundamentals of applied probability and random processes

CERN Document Server

Ibe, Oliver

2005-01-01

This book is based on the premise that engineers use probability as a modeling tool, and that probability can be applied to the solution of engineering problems. Engineers and students studying probability and random processes also need to analyze data, and thus need some knowledge of statistics. This book is designed to provide students with a thorough grounding in probability and stochastic processes, demonstrate their applicability to real-world problems, and introduce the basics of statistics. The book''s clear writing style and homework problems make it ideal for the classroom or for self-study.* Good and solid introduction to probability theory and stochastic processes * Logically organized; writing is presented in a clear manner * Choice of topics is comprehensive within the area of probability * Ample homework problems are organized into chapter sections

Estimating inverse probability weights using super learner when weight-model specification is unknown in a marginal structural Cox model context.

Science.gov (United States)

Karim, Mohammad Ehsanul; Platt, Robert W

2017-06-15

Correct specification of the inverse probability weighting (IPW) model is necessary for consistent inference from a marginal structural Cox model (MSCM). In practical applications, researchers are typically unaware of the true specification of the weight model. Nonetheless, IPWs are commonly estimated using parametric models, such as the main-effects logistic regression model. In practice, assumptions underlying such models may not hold and data-adaptive statistical learning methods may provide an alternative. Many candidate statistical learning approaches are available in the literature. However, the optimal approach for a given dataset is impossible to predict. Super learner (SL) has been proposed as a tool for selecting an optimal learner from a set of candidates using cross-validation. In this study, we evaluate the usefulness of a SL in estimating IPW in four different MSCM simulation scenarios, in which we varied the specification of the true weight model specification (linear and/or additive). Our simulations show that, in the presence of weight model misspecification, with a rich and diverse set of candidate algorithms, SL can generally offer a better alternative to the commonly used statistical learning approaches in terms of MSE as well as the coverage probabilities of the estimated effect in an MSCM. The findings from the simulation studies guided the application of the MSCM in a multiple sclerosis cohort from British Columbia, Canada (1995-2008), to estimate the impact of beta-interferon treatment in delaying disability progression. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Performance of people with diabetes in the labor market: An empirical approach controlling for complications.

Science.gov (United States)

Rodríguez-Sánchez, Beatriz; Cantarero-Prieto, David

2017-11-01

This paper introduces a framework for modelling the impact that diabetes has on employment status and wages, improving the existing literature by controlling for diabetes-related complications. Using the last wave of the Spanish National Health Survey, we find that 1710 adults out of the original sample of 36,087 have diabetes, reporting higher rates of unemployment. Our empirical results suggest that persons with diabetes, compared with non-diabetic persons, have poorer labor outcomes in terms of length of unemployment and lower income. However, diabetes is not significantly associated with unemployment probabilities, suggesting that the burden of diabetes on employment is mediated by lifestyle factors and clinical and functional complications. In addition, there are mixed outcomes to this econometric approach, depending on age and gender, among other factors. This interesting finding has several implications for research and policy on strategies to get lower health inequalities. Copyright © 2017 Elsevier B.V. All rights reserved.

Upper Bounds for Ruin Probability with Stochastic Investment Return

Institute of Scientific and Technical Information of China (English)

ZHANG Lihong

2005-01-01

Risk models with stochastic investment return are widely held in practice, as well as in more challenging research fields. Risk theory is mainly concerned with ruin probability, and a tight bound for ruin probability is the best for practical use. This paper presents a discrete time risk model with stochastic investment return. Conditional expectation properties and martingale inequalities are used to obtain both exponential and non-exponential upper bounds for the ruin probability.

Sensitivity of the probability of failure to probability of detection curve regions

International Nuclear Information System (INIS)

Garza, J.; Millwater, H.

2016-01-01

Non-destructive inspection (NDI) techniques have been shown to play a vital role in fracture control plans, structural health monitoring, and ensuring availability and reliability of piping, pressure vessels, mechanical and aerospace equipment. Probabilistic fatigue simulations are often used in order to determine the efficacy of an inspection procedure with the NDI method modeled as a probability of detection (POD) curve. These simulations can be used to determine the most advantageous NDI method for a given application. As an aid to this process, a first order sensitivity method of the probability-of-failure (POF) with respect to regions of the POD curve (lower tail, middle region, right tail) is developed and presented here. The sensitivity method computes the partial derivative of the POF with respect to a change in each region of a POD or multiple POD curves. The sensitivities are computed at no cost by reusing the samples from an existing Monte Carlo (MC) analysis. A numerical example is presented considering single and multiple inspections. - Highlights: • Sensitivities of probability-of-failure to a region of probability-of-detection curve. • The sensitivities are computed with negligible cost. • Sensitivities identify the important region of a POD curve. • Sensitivities can be used as a guide to selecting the optimal POD curve.

An Empirical Model for Estimating the Probability of Electrical Short Circuits from Tin Whiskers. Part 2

Science.gov (United States)

Courey, Karim; Wright, Clara; Asfour, Shihab; Onar, Arzu; Bayliss, Jon; Ludwig, Larry

2009-01-01

In this experiment, an empirical model to quantify the probability of occurrence of an electrical short circuit from tin whiskers as a function of voltage was developed. This empirical model can be used to improve existing risk simulation models. FIB and TEM images of a tin whisker confirm the rare polycrystalline structure on one of the three whiskers studied. FIB cross-section of the card guides verified that the tin finish was bright tin.

Human Error Probability Assessment During Maintenance Activities of Marine Systems

Directory of Open Access Journals (Sweden)

Rabiul Islam

2018-03-01

Full Text Available Background: Maintenance operations on-board ships are highly demanding. Maintenance operations are intensive activities requiring high man–machine interactions in challenging and evolving conditions. The evolving conditions are weather conditions, workplace temperature, ship motion, noise and vibration, and workload and stress. For example, extreme weather condition affects seafarers' performance, increasing the chances of error, and, consequently, can cause injuries or fatalities to personnel. An effective human error probability model is required to better manage maintenance on-board ships. The developed model would assist in developing and maintaining effective risk management protocols. Thus, the objective of this study is to develop a human error probability model considering various internal and external factors affecting seafarers' performance. Methods: The human error probability model is developed using probability theory applied to Bayesian network. The model is tested using the data received through the developed questionnaire survey of >200 experienced seafarers with >5 years of experience. The model developed in this study is used to find out the reliability of human performance on particular maintenance activities. Results: The developed methodology is tested on the maintenance of marine engine's cooling water pump for engine department and anchor windlass for deck department. In the considered case studies, human error probabilities are estimated in various scenarios and the results are compared between the scenarios and the different seafarer categories. The results of the case studies for both departments are also compared. Conclusion: The developed model is effective in assessing human error probabilities. These probabilities would get dynamically updated as and when new information is available on changes in either internal (i.e., training, experience, and fatigue or external (i.e., environmental and operational conditions

Probability concepts in quality risk management.

Science.gov (United States)

Claycamp, H Gregg

2012-01-01

Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although risk is generally a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management tools are relatively silent on the meaning and uses of "probability." The probability concept is typically applied by risk managers as a combination of frequency-based calculation and a "degree of belief" meaning of probability. Probability as a concept that is crucial for understanding and managing risk is discussed through examples from the most general, scenario-defining and ranking tools that use probability implicitly to more specific probabilistic tools in risk management. A rich history of probability in risk management applied to other fields suggests that high-quality risk management decisions benefit from the implementation of more thoughtful probability concepts in both risk modeling and risk management. Essentially any concept of risk is built on fundamental concepts of chance, likelihood, or probability. Although "risk" generally describes a probability of loss of something of value, given that a risk-generating event will occur or has occurred, it is ironic that the quality risk management literature and guidelines on quality risk management methodologies and respective tools focus on managing severity but are relatively silent on the in-depth meaning and uses of "probability." Pharmaceutical manufacturers are expanding their use of quality risk management to identify and manage risks to the patient that might occur in phases of the pharmaceutical life cycle from drug development to manufacture, marketing to product discontinuation. A probability concept is typically applied by risk managers as a combination of data-based measures of probability and a subjective "degree of belief" meaning of probability. Probability as

MASTER: a model to improve and standardize clinical breakpoints for antimicrobial susceptibility testing using forecast probabilities.

Science.gov (United States)

Blöchliger, Nicolas; Keller, Peter M; Böttger, Erik C; Hombach, Michael

2017-09-01

The procedure for setting clinical breakpoints (CBPs) for antimicrobial susceptibility has been poorly standardized with respect to population data, pharmacokinetic parameters and clinical outcome. Tools to standardize CBP setting could result in improved antibiogram forecast probabilities. We propose a model to estimate probabilities for methodological categorization errors and defined zones of methodological uncertainty (ZMUs), i.e. ranges of zone diameters that cannot reliably be classified. The impact of ZMUs on methodological error rates was used for CBP optimization. The model distinguishes theoretical true inhibition zone diameters from observed diameters, which suffer from methodological variation. True diameter distributions are described with a normal mixture model. The model was fitted to observed inhibition zone diameters of clinical Escherichia coli strains. Repeated measurements for a quality control strain were used to quantify methodological variation. For 9 of 13 antibiotics analysed, our model predicted error rates of  0.1% for ampicillin, cefoxitin, cefuroxime and amoxicillin/clavulanic acid. Increasing the susceptible CBP (cefoxitin) and introducing ZMUs (ampicillin, cefuroxime, amoxicillin/clavulanic acid) decreased error rates to < 0.1%. ZMUs contained low numbers of isolates for ampicillin and cefuroxime (3% and 6%), whereas the ZMU for amoxicillin/clavulanic acid contained 41% of all isolates and was considered not practical. We demonstrate that CBPs can be improved and standardized by minimizing methodological categorization error rates. ZMUs may be introduced if an intermediate zone is not appropriate for pharmacokinetic/pharmacodynamic or drug dosing reasons. Optimized CBPs will provide a standardized antibiotic susceptibility testing interpretation at a defined level of probability. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For

Hydrological model calibration for flood prediction in current and future climates using probability distributions of observed peak flows and model based rainfall

Science.gov (United States)

Haberlandt, Uwe; Wallner, Markus; Radtke, Imke

2013-04-01

Derived flood frequency analysis based on continuous hydrological modelling is very demanding regarding the required length and temporal resolution of precipitation input data. Often such flood predictions are obtained using long precipitation time series from stochastic approaches or from regional climate models as input. However, the calibration of the hydrological model is usually done using short time series of observed data. This inconsistent employment of different data types for calibration and application of a hydrological model increases its uncertainty. Here, it is proposed to calibrate a hydrological model directly on probability distributions of observed peak flows using model based rainfall in line with its later application. Two examples are given to illustrate the idea. The first one deals with classical derived flood frequency analysis using input data from an hourly stochastic rainfall model. The second one concerns a climate impact analysis using hourly precipitation from a regional climate model. The results show that: (I) the same type of precipitation input data should be used for calibration and application of the hydrological model, (II) a model calibrated on extreme conditions works quite well for average conditions but not vice versa, (III) the calibration of the hydrological model using regional climate model data works as an implicit bias correction method and (IV) the best performance for flood estimation is usually obtained when model based precipitation and observed probability distribution of peak flows are used for model calibration.

Upgrading Probability via Fractions of Events

Directory of Open Access Journals (Sweden)

Frič Roman

2016-08-01

Full Text Available The influence of “Grundbegriffe” by A. N. Kolmogorov (published in 1933 on education in the area of probability and its impact on research in stochastics cannot be overestimated. We would like to point out three aspects of the classical probability theory “calling for” an upgrade: (i classical random events are black-and-white (Boolean; (ii classical random variables do not model quantum phenomena; (iii basic maps (probability measures and observables { dual maps to random variables have very different “mathematical nature”. Accordingly, we propose an upgraded probability theory based on Łukasiewicz operations (multivalued logic on events, elementary category theory, and covering the classical probability theory as a special case. The upgrade can be compared to replacing calculations with integers by calculations with rational (and real numbers. Namely, to avoid the three objections, we embed the classical (Boolean random events (represented by the f0; 1g-valued indicator functions of sets into upgraded random events (represented by measurable {0; 1}-valued functions, the minimal domain of probability containing “fractions” of classical random events, and we upgrade the notions of probability measure and random variable.

p-adic probability interpretation of Bell's inequality

International Nuclear Information System (INIS)

Khrennikov, A.

1995-01-01

We study the violation of Bell's inequality using a p-adic generalization of the theory of probability. p-adic probability is introduced as a limit of relative frequencies but this limit exists with respect to a p-adic metric. In particular, negative probability distributions are well defined on the basis of the frequency definition. This new type of stochastics can be used to describe hidden-variables distributions of some quantum models. If the hidden variables have a p-adic probability distribution, Bell's inequality is not valid and it is not necessary to discuss the experimental violations of this inequality. ((orig.))

VOLCANIC RISK ASSESSMENT - PROBABILITY AND CONSEQUENCES

International Nuclear Information System (INIS)

G.A. Valentine; F.V. Perry; S. Dartevelle

2005-01-01

Risk is the product of the probability and consequences of an event. Both of these must be based upon sound science that integrates field data, experiments, and modeling, but must also be useful to decision makers who likely do not understand all aspects of the underlying science. We review a decision framework used in many fields such as performance assessment for hazardous and/or radioactive waste disposal sites that can serve to guide the volcanological community towards integrated risk assessment. In this framework the underlying scientific understanding of processes that affect probability and consequences drive the decision-level results, but in turn these results can drive focused research in areas that cause the greatest level of uncertainty at the decision level. We review two examples of the determination of volcanic event probability: (1) probability of a new volcano forming at the proposed Yucca Mountain radioactive waste repository, and (2) probability that a subsurface repository in Japan would be affected by the nearby formation of a new stratovolcano. We also provide examples of work on consequences of explosive eruptions, within the framework mentioned above. These include field-based studies aimed at providing data for ''closure'' of wall rock erosion terms in a conduit flow model, predictions of dynamic pressure and other variables related to damage by pyroclastic flow into underground structures, and vulnerability criteria for structures subjected to conditions of explosive eruption. Process models (e.g., multiphase flow) are important for testing the validity or relative importance of possible scenarios in a volcanic risk assessment. We show how time-dependent multiphase modeling of explosive ''eruption'' of basaltic magma into an open tunnel (drift) at the Yucca Mountain repository provides insight into proposed scenarios that include the development of secondary pathways to the Earth's surface. Addressing volcanic risk within a decision

Surgical Apgar Score Predicts Postoperative Complications in ...

African Journals Online (AJOL)

complications were determined during the thirty day post operative period. ... An ideal model to predict postoperative complications ... their SAS for purposes of risk stratification; high risk. (0-4), medium .... surgical audit (9,14). Serial monitoring ...

Application of wildfire spread and behavior models to assess fire probability and severity in the Mediterranean region

Science.gov (United States)

Salis, Michele; Arca, Bachisio; Bacciu, Valentina; Spano, Donatella; Duce, Pierpaolo; Santoni, Paul; Ager, Alan; Finney, Mark

2010-05-01

Characterizing the spatial pattern of large fire occurrence and severity is an important feature of the fire management planning in the Mediterranean region. The spatial characterization of fire probabilities, fire behavior distributions and value changes are key components for quantitative risk assessment and for prioritizing fire suppression resources, fuel treatments and law enforcement. Because of the growing wildfire severity and frequency in recent years (e.g.: Portugal, 2003 and 2005; Italy and Greece, 2007 and 2009), there is an increasing demand for models and tools that can aid in wildfire prediction and prevention. Newer wildfire simulation systems offer promise in this regard, and allow for fine scale modeling of wildfire severity and probability. Several new applications has resulted from the development of a minimum travel time (MTT) fire spread algorithm (Finney, 2002), that models the fire growth searching for the minimum time for fire to travel among nodes in a 2D network. The MTT approach makes computationally feasible to simulate thousands of fires and generate burn probability and fire severity maps over large areas. The MTT algorithm is imbedded in a number of research and fire modeling applications. High performance computers are typically used for MTT simulations, although the algorithm is also implemented in the FlamMap program (www.fire.org). In this work, we described the application of the MTT algorithm to estimate spatial patterns of burn probability and to analyze wildfire severity in three fire prone areas of the Mediterranean Basin, specifically Sardinia (Italy), Sicily (Italy) and Corsica (France) islands. We assembled fuels and topographic data for the simulations in 500 x 500 m grids for the study areas. The simulations were run using 100,000 ignitions under weather conditions that replicated severe and moderate weather conditions (97th and 70th percentile, July and August weather, 1995-2007). We used both random ignition locations

Empirical probability model of cold plasma environment in the Jovian magnetosphere

Science.gov (United States)

Futaana, Yoshifumi; Wang, Xiao-Dong; Barabash, Stas; Roussos, Elias; Truscott, Pete

2015-04-01

We analyzed the Galileo PLS dataset to produce a new cold plasma environment model for the Jovian magneto- sphere. Although there exist many sophisticated radiation models, treating energetic plasma (e.g. JOSE, GIRE, or Salammbo), only a limited number of simple models has been utilized for cold plasma environment. By extend- ing the existing cold plasma models toward the probability domain, we can predict the extreme periods of Jovian environment by specifying the percentile of the environmental parameters. The new model was produced in the following procedure. We first referred to the existing cold plasma models of Divine and Garrett, 1983 (DG83) or Bagenal and Delamere 2011 (BD11). These models are scaled to fit the statistical median of the parameters obtained from Galileo PLS data. The scaled model (also called as "mean model") indicates the median environment of Jovian magnetosphere. Then, assuming that the deviations in the Galileo PLS parameters are purely due to variations in the environment, we extended the mean model toward the percentile domain. The input parameter of the model is simply the position of the spacecraft (distance, magnetic longitude and lati- tude) and the specific percentile (e.g. 0.5 for the mean model). All the parameters in the model are described in mathematical forms; therefore the needed computational resources are quite low. The new model can be used for assessing the JUICE mission profile. The spatial extent of the model covers the main phase of the JUICE mission; namely from the Europa orbit to 40 Rj (where Rj is the radius of Jupiter). In addition, theoretical extensions toward the latitudinal direction are also included in the model to support the high latitude orbit of the JUICE spacecraft.

Analytical models of probability distribution and excess noise factor of solid state photomultiplier signals with crosstalk

International Nuclear Information System (INIS)

Vinogradov, S.

2012-01-01

Silicon Photomultipliers (SiPM), also called Solid State Photomultipliers (SSPM), are based on Geiger mode avalanche breakdown that is limited by a strong negative feedback. An SSPM can detect and resolve single photons due to the high gain and ultra-low excess noise of avalanche multiplication in this mode. Crosstalk and afterpulsing processes associated with the high gain introduce specific excess noise and deteriorate the photon number resolution of the SSPM. The probabilistic features of these processes are widely studied because of its significance for the SSPM design, characterization, optimization and application, but the process modeling is mostly based on Monte Carlo simulations and numerical methods. In this study, crosstalk is considered to be a branching Poisson process, and analytical models of probability distribution and excess noise factor (ENF) of SSPM signals based on the Borel distribution as an advance on the geometric distribution models are presented and discussed. The models are found to be in a good agreement with the experimental probability distributions for dark counts and a few photon spectrums in a wide range of fired pixels number as well as with observed super-linear behavior of crosstalk ENF.

Allelic drop-out probabilities estimated by logistic regression

DEFF Research Database (Denmark)

Tvedebrink, Torben; Eriksen, Poul Svante; Asplund, Maria

2012-01-01

We discuss the model for estimating drop-out probabilities presented by Tvedebrink et al. [7] and the concerns, that have been raised. The criticism of the model has demonstrated that the model is not perfect. However, the model is very useful for advanced forensic genetic work, where allelic drop-out...... is occurring. With this discussion, we hope to improve the drop-out model, so that it can be used for practical forensic genetics and stimulate further discussions. We discuss how to estimate drop-out probabilities when using a varying number of PCR cycles and other experimental conditions....

Classical probabilities for Majorana and Weyl spinors

International Nuclear Information System (INIS)

Wetterich, C.

2011-01-01

Highlights: → Map of classical statistical Ising model to fermionic quantum field theory. → Lattice-regularized real Grassmann functional integral for single Weyl spinor. → Emerging complex structure characteristic for quantum physics. → A classical statistical ensemble describes a quantum theory. - Abstract: We construct a map between the quantum field theory of free Weyl or Majorana fermions and the probability distribution of a classical statistical ensemble for Ising spins or discrete bits. More precisely, a Grassmann functional integral based on a real Grassmann algebra specifies the time evolution of the real wave function q τ (t) for the Ising states τ. The time dependent probability distribution of a generalized Ising model obtains as p τ (t)=q τ 2 (t). The functional integral employs a lattice regularization for single Weyl or Majorana spinors. We further introduce the complex structure characteristic for quantum mechanics. Probability distributions of the Ising model which correspond to one or many propagating fermions are discussed explicitly. Expectation values of observables can be computed equivalently in the classical statistical Ising model or in the quantum field theory for fermions.

Discrete probability models and methods probability on graphs and trees, Markov chains and random fields, entropy and coding

CERN Document Server

Brémaud, Pierre

2017-01-01

The emphasis in this book is placed on general models (Markov chains, random fields, random graphs), universal methods (the probabilistic method, the coupling method, the Stein-Chen method, martingale methods, the method of types) and versatile tools (Chernoff's bound, Hoeffding's inequality, Holley's inequality) whose domain of application extends far beyond the present text. Although the examples treated in the book relate to the possible applications, in the communication and computing sciences, in operations research and in physics, this book is in the first instance concerned with theory. The level of the book is that of a beginning graduate course. It is self-contained, the prerequisites consisting merely of basic calculus (series) and basic linear algebra (matrices). The reader is not assumed to be trained in probability since the first chapters give in considerable detail the background necessary to understand the rest of the book. .

K-shell ionization probability in energetic nearly symmetric heavy-ion collisions

International Nuclear Information System (INIS)

Tserruya, I.; Schmidt-Boecking, H.; Schuch, R.

1977-01-01

Impact parameter dependent K-x-ray emission probabilities for the projectile and target atoms have been measured in 35 MeV Cl on Cl, Cl on Ti and Cl on Ni collisions. The sum of projectile plus target K-shell ionization probability is taken as a measure of the total 2psigma ionization probability. The 2pπ-2psigma totational coupling model is in clear disagreement with the present results. On the other hand the sum of probabilities is reproduced both in shape and absolute magnitude by the statistical model for inner-shell ionization. The K-shell ionization probability of the higher -Z collision partner is well described by this model including the 2psigma-1ssigma vacancy sharing probability calculated as a function of the impact parameter. (author)

Contributions to quantum probability

Energy Technology Data Exchange (ETDEWEB)

Fritz, Tobias

2010-06-25

Chapter 1: On the existence of quantum representations for two dichotomic measurements. Under which conditions do outcome probabilities of measurements possess a quantum-mechanical model? This kind of problem is solved here for the case of two dichotomic von Neumann measurements which can be applied repeatedly to a quantum system with trivial dynamics. The solution uses methods from the theory of operator algebras and the theory of moment problems. The ensuing conditions reveal surprisingly simple relations between certain quantum-mechanical probabilities. It also shown that generally, none of these relations holds in general probabilistic models. This result might facilitate further experimental discrimination between quantum mechanics and other general probabilistic theories. Chapter 2: Possibilistic Physics. I try to outline a framework for fundamental physics where the concept of probability gets replaced by the concept of possibility. Whereas a probabilistic theory assigns a state-dependent probability value to each outcome of each measurement, a possibilistic theory merely assigns one of the state-dependent labels ''possible to occur'' or ''impossible to occur'' to each outcome of each measurement. It is argued that Spekkens' combinatorial toy theory of quantum mechanics is inconsistent in a probabilistic framework, but can be regarded as possibilistic. Then, I introduce the concept of possibilistic local hidden variable models and derive a class of possibilistic Bell inequalities which are violated for the possibilistic Popescu-Rohrlich boxes. The chapter ends with a philosophical discussion on possibilistic vs. probabilistic. It can be argued that, due to better falsifiability properties, a possibilistic theory has higher predictive power than a probabilistic one. Chapter 3: The quantum region for von Neumann measurements with postselection. It is determined under which conditions a probability distribution on a

Probability problems in seismic risk analysis and load combinations for nuclear power plants

International Nuclear Information System (INIS)

George, L.L.

1983-01-01

This workshop describes some probability problems in power plant reliability and maintenance analysis. The problems are seismic risk analysis, loss of load probability, load combinations, and load sharing. The seismic risk problem is to compute power plant reliability given an earthquake and the resulting risk. Component survival occurs if its peak random response to the earthquake does not exceed its strength. Power plant survival is a complicated Boolean function of component failures and survivals. The responses and strengths of components are dependent random processes, and the peak responses are maxima of random processes. The resulting risk is the expected cost of power plant failure

Spatial probability aids visual stimulus discrimination

Directory of Open Access Journals (Sweden)

Michael Druker

2010-08-01

Full Text Available We investigated whether the statistical predictability of a target's location would influence how quickly and accurately it was classified. Recent results have suggested that spatial probability can be a cue for the allocation of attention in visual search. One explanation for probability cuing is spatial repetition priming. In our two experiments we used probability distributions that were continuous across the display rather than relying on a few arbitrary screen locations. This produced fewer spatial repeats and allowed us to dissociate the effect of a high probability location from that of short-term spatial repetition. The task required participants to quickly judge the color of a single dot presented on a computer screen. In Experiment 1, targets were more probable in an off-center hotspot of high probability that gradually declined to a background rate. Targets garnered faster responses if they were near earlier target locations (priming and if they were near the high probability hotspot (probability cuing. In Experiment 2, target locations were chosen on three concentric circles around fixation. One circle contained 80% of targets. The value of this ring distribution is that it allowed for a spatially restricted high probability zone in which sequentially repeated trials were not likely to be physically close. Participant performance was sensitive to the high-probability circle in addition to the expected effects of eccentricity and the distance to recent targets. These two experiments suggest that inhomogeneities in spatial probability can be learned and used by participants on-line and without prompting as an aid for visual stimulus discrimination and that spatial repetition priming is not a sufficient explanation for this effect. Future models of attention should consider explicitly incorporating the probabilities of targets locations and features.

A comparison of the probability distribution of observed substorm magnitude with that predicted by a minimal substorm model

Directory of Open Access Journals (Sweden)

S. K. Morley

2007-11-01

Full Text Available We compare the probability distributions of substorm magnetic bay magnitudes from observations and a minimal substorm model. The observed distribution was derived previously and independently using the IL index from the IMAGE magnetometer network. The model distribution is derived from a synthetic AL index time series created using real solar wind data and a minimal substorm model, which was previously shown to reproduce observed substorm waiting times. There are two free parameters in the model which scale the contributions to AL from the directly-driven DP2 electrojet and loading-unloading DP1 electrojet, respectively. In a limited region of the 2-D parameter space of the model, the probability distribution of modelled substorm bay magnitudes is not significantly different to the observed distribution. The ranges of the two parameters giving acceptable (95% confidence level agreement are consistent with expectations using results from other studies. The approximately linear relationship between the two free parameters over these ranges implies that the substorm magnitude simply scales linearly with the solar wind power input at the time of substorm onset.

Establishment probability in newly founded populations

Directory of Open Access Journals (Sweden)

Gusset Markus

2012-06-01

Full Text Available Abstract Background Establishment success in newly founded populations relies on reaching the established phase, which is defined by characteristic fluctuations of the population’s state variables. Stochastic population models can be used to quantify the establishment probability of newly founded populations; however, so far no simple but robust method for doing so existed. To determine a critical initial number of individuals that need to be released to reach the established phase, we used a novel application of the “Wissel plot”, where –ln(1 – P0(t is plotted against time t. This plot is based on the equation P0t=1–c1e–ω1t, which relates the probability of extinction by time t, P0(t, to two constants: c1 describes the probability of a newly founded population to reach the established phase, whereas ω1 describes the population’s probability of extinction per short time interval once established. Results For illustration, we applied the method to a previously developed stochastic population model of the endangered African wild dog (Lycaon pictus. A newly founded population reaches the established phase if the intercept of the (extrapolated linear parts of the “Wissel plot” with the y-axis, which is –ln(c1, is negative. For wild dogs in our model, this is the case if a critical initial number of four packs, consisting of eight individuals each, are released. Conclusions The method we present to quantify the establishment probability of newly founded populations is generic and inferences thus are transferable to other systems across the field of conservation biology. In contrast to other methods, our approach disaggregates the components of a population’s viability by distinguishing establishment from persistence.

Bayesian Probability Theory

Science.gov (United States)

von der Linden, Wolfgang; Dose, Volker; von Toussaint, Udo

2014-06-01

Preface; Part I. Introduction: 1. The meaning of probability; 2. Basic definitions; 3. Bayesian inference; 4. Combinatrics; 5. Random walks; 6. Limit theorems; 7. Continuous distributions; 8. The central limit theorem; 9. Poisson processes and waiting times; Part II. Assigning Probabilities: 10. Transformation invariance; 11. Maximum entropy; 12. Qualified maximum entropy; 13. Global smoothness; Part III. Parameter Estimation: 14. Bayesian parameter estimation; 15. Frequentist parameter estimation; 16. The Cramer-Rao inequality; Part IV. Testing Hypotheses: 17. The Bayesian way; 18. The frequentist way; 19. Sampling distributions; 20. Bayesian vs frequentist hypothesis tests; Part V. Real World Applications: 21. Regression; 22. Inconsistent data; 23. Unrecognized signal contributions; 24. Change point problems; 25. Function estimation; 26. Integral equations; 27. Model selection; 28. Bayesian experimental design; Part VI. Probabilistic Numerical Techniques: 29. Numerical integration; 30. Monte Carlo methods; 31. Nested sampling; Appendixes; References; Index.

Grading the probabilities of credit default risk for Malaysian listed companies by using the KMV-Merton model

Science.gov (United States)

Anuwar, Muhammad Hafidz; Jaffar, Maheran Mohd

2017-08-01

This paper provides an overview for the assessment of credit risk specific to the banks. In finance, risk is a term to reflect the potential of financial loss. The risk of default on loan may increase when a company does not make a payment on that loan when the time comes. Hence, this framework analyses the KMV-Merton model to estimate the probabilities of default for Malaysian listed companies. In this way, banks can verify the ability of companies to meet their loan commitments in order to overcome bad investments and financial losses. This model has been applied to all Malaysian listed companies in Bursa Malaysia for estimating the credit default probabilities of companies and compare with the rating given by the rating agency, which is RAM Holdings Berhad to conform to reality. Then, the significance of this study is a credit risk grade is proposed by using the KMV-Merton model for the Malaysian listed companies.

School and conference on probability theory

International Nuclear Information System (INIS)

Lawler, G.F.

2004-01-01

This volume includes expanded lecture notes from the School and Conference in Probability Theory held at ICTP in May, 2001. Probability theory is a very large area, too large for a single school and conference. The organizers, G. Lawler, C. Newman, and S. Varadhan chose to focus on a number of active research areas that have their roots in statistical physics. The pervasive theme in these lectures is trying to find the large time or large space behaviour of models defined on discrete lattices. Usually the definition of the model is relatively simple: either assigning a particular weight to each possible configuration (equilibrium statistical mechanics) or specifying the rules under which the system evolves (nonequilibrium statistical mechanics). Interacting particle systems is the area of probability that studies the evolution of particles (either finite or infinite in number) under random motions. The evolution of particles depends on the positions of the other particles; often one assumes that it depends only on the particles that are close to the particular particle. Thomas Liggett's lectures give an introduction to this very large area. Claudio Landim's follows up by discussing hydrodynamic limits of particle systems. The goal of this area is to describe the long time, large system size dynamics in terms of partial differential equations. The area of random media is concerned with the properties of materials or environments that are not homogeneous. Percolation theory studies one of the simplest stated models for impurities - taking a lattice and removing some of the vertices or bonds. Luiz Renato G. Fontes and Vladas Sidoravicius give a detailed introduction to this area. Random walk in random environment combines two sources of randomness - a particle performing stochastic motion in which the transition probabilities depend on position and have been chosen from some probability distribution. Alain-Sol Sznitman gives a survey of recent developments in this

Cladding failure probability modeling for risk evaluations of fast reactors

International Nuclear Information System (INIS)

Mueller, C.J.; Kramer, J.M.

1987-01-01

This paper develops the methodology to incorporate cladding failure data and associated modeling into risk evaluations of liquid metal-cooled fast reactors (LMRs). Current US innovative designs for metal-fueled pool-type LMRs take advantage of inherent reactivity feedback mechanisms to limit reactor temperature increases in response to classic anticipated-transient-without-scram (ATWS) initiators. Final shutdown without reliance on engineered safety features can then be accomplished if sufficient time is available for operator intervention to terminate fission power production and/or provide auxiliary cooling prior to significant core disruption. Coherent cladding failure under the sustained elevated temperatures of ATWS events serves as one indicator of core disruption. In this paper we combine uncertainties in cladding failure data with uncertainties in calculations of ATWS cladding temperature conditions to calculate probabilities of cladding failure as a function of the time for accident recovery

Ruin probability with claims modeled by a stationary ergodic stable process

NARCIS (Netherlands)

Mikosch, T.; Samorodnitsky, G.

2000-01-01

For a random walk with negative drift we study the exceedance probability (ruin probability) of a high threshold. The steps of this walk (claim sizes) constitute a stationary ergodic stable process. We study how ruin occurs in this situation and evaluate the asymptotic behavior of the ruin

Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization

Science.gov (United States)

Cavagnaro, Daniel R.; Pitt, Mark A.; Gonzalez, Richard; Myung, Jay I.

2014-01-01

Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments to investigate the extent to which different parametric forms of the probability weighting function can be discriminated using adaptive design optimization, a computer-based methodology that identifies and exploits model differences for the purpose of model discrimination. The simulation experiments show that the correct (data-generating) form can be conclusively discriminated from its competitors. The results of an empirical experiment reveal heterogeneity between participants in terms of the functional form, with two models (Prelec-2, Linear in Log Odds) emerging as the most common best-fitting models. The findings shed light on assumptions underlying these models. PMID:24453406

Use of the AIC with the EM algorithm: A demonstration of a probability model selection technique

Energy Technology Data Exchange (ETDEWEB)

Glosup, J.G.; Axelrod M.C. [Lawrence Livermore National Lab., CA (United States)

1994-11-15

The problem of discriminating between two potential probability models, a Gaussian distribution and a mixture of Gaussian distributions, is considered. The focus of our interest is a case where the models are potentially non-nested and the parameters of the mixture model are estimated through the EM algorithm. The AIC, which is frequently used as a criterion for discriminating between non-nested models, is modified to work with the EM algorithm and is shown to provide a model selection tool for this situation. A particular problem involving an infinite mixture distribution known as Middleton`s Class A model is used to demonstrate the effectiveness and limitations of this method.

Consistent probabilities in loop quantum cosmology

International Nuclear Information System (INIS)

Craig, David A; Singh, Parampreet

2013-01-01

A fundamental issue for any quantum cosmological theory is to specify how probabilities can be assigned to various quantum events or sequences of events such as the occurrence of singularities or bounces. In previous work, we have demonstrated how this issue can be successfully addressed within the consistent histories approach to quantum theory for Wheeler–DeWitt-quantized cosmological models. In this work, we generalize that analysis to the exactly solvable loop quantization of a spatially flat, homogeneous and isotropic cosmology sourced with a massless, minimally coupled scalar field known as sLQC. We provide an explicit, rigorous and complete decoherent-histories formulation for this model and compute the probabilities for the occurrence of a quantum bounce versus a singularity. Using the scalar field as an emergent internal time, we show for generic states that the probability for a singularity to occur in this model is zero, and that of a bounce is unity, complementing earlier studies of the expectation values of the volume and matter density in this theory. We also show from the consistent histories point of view that all states in this model, whether quantum or classical, achieve arbitrarily large volume in the limit of infinite ‘past’ or ‘future’ scalar ‘time’, in the sense that the wave function evaluated at any arbitrary fixed value of the volume vanishes in that limit. Finally, we briefly discuss certain misconceptions concerning the utility of the consistent histories approach in these models. (paper)

[Application of Bayes Probability Model in Differentiation of Yin and Yang Jaundice Syndromes in Neonates].

Science.gov (United States)

Mu, Chun-sun; Zhang, Ping; Kong, Chun-yan; Li, Yang-ning

2015-09-01

To study the application of Bayes probability model in differentiating yin and yang jaundice syndromes in neonates. Totally 107 jaundice neonates who admitted to hospital within 10 days after birth were assigned to two groups according to syndrome differentiation, 68 in the yang jaundice syndrome group and 39 in the yin jaundice syndrome group. Data collected for neonates were factors related to jaundice before, during and after birth. Blood routines, liver and renal functions, and myocardial enzymes were tested on the admission day or the next day. Logistic regression model and Bayes discriminating analysis were used to screen factors important for yin and yang jaundice syndrome differentiation. Finally, Bayes probability model for yin and yang jaundice syndromes was established and assessed. Factors important for yin and yang jaundice syndrome differentiation screened by Logistic regression model and Bayes discriminating analysis included mothers' age, mother with gestational diabetes mellitus (GDM), gestational age, asphyxia, or ABO hemolytic diseases, red blood cell distribution width (RDW-SD), platelet-large cell ratio (P-LCR), serum direct bilirubin (DBIL), alkaline phosphatase (ALP), cholinesterase (CHE). Bayes discriminating analysis was performed by SPSS to obtain Bayes discriminant function coefficient. Bayes discriminant function was established according to discriminant function coefficients. Yang jaundice syndrome: y1= -21. 701 +2. 589 x mother's age + 1. 037 x GDM-17. 175 x asphyxia + 13. 876 x gestational age + 6. 303 x ABO hemolytic disease + 2.116 x RDW-SD + 0. 831 x DBIL + 0. 012 x ALP + 1. 697 x LCR + 0. 001 x CHE; Yin jaundice syndrome: y2= -33. 511 + 2.991 x mother's age + 3.960 x GDM-12. 877 x asphyxia + 11. 848 x gestational age + 1. 820 x ABO hemolytic disease +2. 231 x RDW-SD +0. 999 x DBIL +0. 023 x ALP +1. 916 x LCR +0. 002 x CHE. Bayes discriminant function was hypothesis tested and got Wilks' λ =0. 393 (P =0. 000). So Bayes

Fixation Probability in a Two-Locus Model by the Ancestral Recombination–Selection Graph

Science.gov (United States)

Lessard, Sabin; Kermany, Amir R.

2012-01-01

We use the ancestral influence graph (AIG) for a two-locus, two-allele selection model in the limit of a large population size to obtain an analytic approximation for the probability of ultimate fixation of a single mutant allele A. We assume that this new mutant is introduced at a given locus into a finite population in which a previous mutant allele B is already segregating with a wild type at another linked locus. We deduce that the fixation probability increases as the recombination rate increases if allele A is either in positive epistatic interaction with B and allele B is beneficial or in no epistatic interaction with B and then allele A itself is beneficial. This holds at least as long as the recombination fraction and the selection intensity are small enough and the population size is large enough. In particular this confirms the Hill–Robertson effect, which predicts that recombination renders more likely the ultimate fixation of beneficial mutants at different loci in a population in the presence of random genetic drift even in the absence of epistasis. More importantly, we show that this is true from weak negative epistasis to positive epistasis, at least under weak selection. In the case of deleterious mutants, the fixation probability decreases as the recombination rate increases. This supports Muller’s ratchet mechanism to explain the accumulation of deleterious mutants in a population lacking recombination. PMID:22095080

On the quantification and efficient propagation of imprecise probabilities resulting from small datasets

Science.gov (United States)

Zhang, Jiaxin; Shields, Michael D.

2018-01-01

This paper addresses the problem of uncertainty quantification and propagation when data for characterizing probability distributions are scarce. We propose a methodology wherein the full uncertainty associated with probability model form and parameter estimation are retained and efficiently propagated. This is achieved by applying the information-theoretic multimodel inference method to identify plausible candidate probability densities and associated probabilities that each method is the best model in the Kullback-Leibler sense. The joint parameter densities for each plausible model are then estimated using Bayes' rule. We then propagate this full set of probability models by estimating an optimal importance sampling density that is representative of all plausible models, propagating this density, and reweighting the samples according to each of the candidate probability models. This is in contrast with conventional methods that try to identify a single probability model that encapsulates the full uncertainty caused by lack of data and consequently underestimate uncertainty. The result is a complete probabilistic description of both aleatory and epistemic uncertainty achieved with several orders of magnitude reduction in computational cost. It is shown how the model can be updated to adaptively accommodate added data and added candidate probability models. The method is applied for uncertainty analysis of plate buckling strength where it is demonstrated how dataset size affects the confidence (or lack thereof) we can place in statistical estimates of response when data are lacking.

The method of modular characteristic direction probabilities in MPACT

Energy Technology Data Exchange (ETDEWEB)

Liu, Z. [School of Nuclear Science and Technology, Xi' an Jiaotong University, No. 28 Xianning west road, Xi' an, Shaanxi 710049 (China); Kochunas, B.; Collins, B.; Downar, T. [Department of Nuclear Engineering and Radiological Sciences, University of Michigan, 2200 Bonisteel, Ann Arbor, MI 48109 (United States); Wu, H. [School of Nuclear Science and Technology, Xi' an Jiaotong University, No. 28 Xianning west road, Xi' an, Shaanxi 710049 (China)

2013-07-01

The method of characteristic direction probabilities (CDP) is based on a modular ray tracing technique which combines the benefits of the collision probability method (CPM) and the method of characteristics (MOC). This past year CDP was implemented in the transport code MPACT for 2-D and 3-D transport calculations. By only coupling the fine mesh regions passed by the characteristic rays in the particular direction, the scale of the probabilities matrix is much smaller compared to the CPM. At the same time, the CDP has the same capacity of dealing with the complicated geometries with the MOC, because the same modular ray tracing techniques are used. Results from the C5G7 benchmark problems are given for different cases to show the accuracy and efficiency of the CDP compared to MOC. For the cases examined, the CDP and MOC methods were seen to differ in k{sub eff} by about 1-20 pcm, and the computational efficiency of the CDP appears to be better than the MOC for some problems. However, in other problems, particularly when the CDP matrices have to be recomputed from changing cross sections, the CDP does not perform as well. This indicates an area of future work. (authors)

Quantum probability measures and tomographic probability densities

NARCIS (Netherlands)

Amosov, GG; Man'ko, [No Value

2004-01-01

Using a simple relation of the Dirac delta-function to generalized the theta-function, the relationship between the tomographic probability approach and the quantum probability measure approach with the description of quantum states is discussed. The quantum state tomogram expressed in terms of the

Infectious complications after out-of-hospital cardiac arrest-A comparison between two target temperatures

DEFF Research Database (Denmark)

Dankiewicz, Josef; Nielsen, Niklas; Linder, Adam

2017-01-01

-to-treat population. Five-hundred patients (53%) developed pneumonia, severe sepsis or septic shock which was associated with mortality in multivariate analysis (Hazard ratio [HR] 1.39; 95%CI 1.13-1.70; p=0.001). There was no statistically significant difference in the incidence of infectious complications between......BACKGROUND: It has been suggested that target temperature management (TTM) increases the probability of infectious complications after cardiac arrest. We aimed to compare the incidence of pneumonia, severe sepsis and septic shock after out-of-hospital cardiac arrest (OHCA) in patients with two...... complications were recorded daily during the ICU-stay. Pneumonia, severe sepsis and septic shock were considered infectious complications. Procalcitonin (PCT) and C-reactive-protein (CRP) levels were measured at 24h, 48h and 72h after cardiac arrest. RESULTS: There were 939 patients in the modified intention...

Theory and analysis of accuracy for the method of characteristics direction probabilities with boundary averaging

International Nuclear Information System (INIS)

Liu, Zhouyu; Collins, Benjamin; Kochunas, Brendan; Downar, Thomas; Xu, Yunlin; Wu, Hongchun

2015-01-01

Highlights: • The CDP combines the benefits of the CPM’s efficiency and the MOC’s flexibility. • Boundary averaging reduces the computation effort with losing minor accuracy. • An analysis model is used to justify the choice of optimize averaging strategy. • Numerical results show the performance and accuracy. - Abstract: The method of characteristic direction probabilities (CDP) combines the benefits of the collision probability method (CPM) and the method of characteristics (MOC) for the solution of the integral form of the Botlzmann Transport Equation. By coupling only the fine regions traversed by the characteristic rays in a particular direction, the computational effort required to calculate the probability matrices and to solve the matrix system is considerably reduced compared to the CPM. Furthermore, boundary averaging is performed to reduce the storage and computation but the capability of dealing with complicated geometries is preserved since the same ray tracing information is used as in MOC. An analysis model for the outgoing angular flux is used to analyze a variety of outgoing angular flux averaging methods for the boundary and to justify the choice of optimize averaging strategy. The boundary average CDP method was then implemented in the Michigan PArallel Characteristic based Transport (MPACT) code to perform 2-D and 3-D transport calculations. The numerical results are given for different cases to show the effect of averaging on the outgoing angular flux, region scalar flux and the eigenvalue. Comparison of the results with the case with no averaging demonstrates that an angular dependent averaging strategy is possible for the CDP to improve its computational performance without compromising the achievable accuracy

Probability-neighbor method of accelerating geometry treatment in reactor Monte Carlo code RMC

International Nuclear Information System (INIS)

She, Ding; Li, Zeguang; Xu, Qi; Wang, Kan; Yu, Ganglin

2011-01-01

Probability neighbor method (PNM) is proposed in this paper to accelerate geometry treatment of Monte Carlo (MC) simulation and validated in self-developed reactor Monte Carlo code RMC. During MC simulation by either ray-tracking or delta-tracking method, large amounts of time are spent in finding out which cell one particle is located in. The traditional way is to search cells one by one with certain sequence defined previously. However, this procedure becomes very time-consuming when the system contains a large number of cells. Considering that particles have different probability to enter different cells, PNM method optimizes the searching sequence, i.e., the cells with larger probability are searched preferentially. The PNM method is implemented in RMC code and the numerical results show that the considerable time of geometry treatment in MC calculation for complicated systems is saved, especially effective in delta-tracking simulation. (author)

Methods for estimating drought streamflow probabilities for Virginia streams

Science.gov (United States)

Austin, Samuel H.

2014-01-01

Maximum likelihood logistic regression model equations used to estimate drought flow probabilities for Virginia streams are presented for 259 hydrologic basins in Virginia. Winter streamflows were used to estimate the likelihood of streamflows during the subsequent drought-prone summer months. The maximum likelihood logistic regression models identify probable streamflows from 5 to 8 months in advance. More than 5 million streamflow daily values collected over the period of record (January 1, 1900 through May 16, 2012) were compiled and analyzed over a minimum 10-year (maximum 112-year) period of record. The analysis yielded the 46,704 equations with statistically significant fit statistics and parameter ranges published in two tables in this report. These model equations produce summer month (July, August, and September) drought flow threshold probabilities as a function of streamflows during the previous winter months (November, December, January, and February). Example calculations are provided, demonstrating how to use the equations to estimate probable streamflows as much as 8 months in advance.

Elephantiasis Nostras Verrucosa (ENV): a complication of congestive heart failure and obesity.

Science.gov (United States)

Baird, Drew; Bode, David; Akers, Troy; Deyoung, Zachariah

2010-01-01

Congestive heart failure (CHF) and obesity are common medical conditions that have many complications and an increasing incidence in the United States. Presented here is a case of a disfiguring skin condition that visually highlights the dermatologic consequences of poorly controlled CHF and obesity. This condition will probably become more common as CHF and obesity increase in the US.

Economic choices reveal probability distortion in macaque monkeys.

Science.gov (United States)

Stauffer, William R; Lak, Armin; Bossaerts, Peter; Schultz, Wolfram

2015-02-18

Economic choices are largely determined by two principal elements, reward value (utility) and probability. Although nonlinear utility functions have been acknowledged for centuries, nonlinear probability weighting (probability distortion) was only recently recognized as a ubiquitous aspect of real-world choice behavior. Even when outcome probabilities are known and acknowledged, human decision makers often overweight low probability outcomes and underweight high probability outcomes. Whereas recent studies measured utility functions and their corresponding neural correlates in monkeys, it is not known whether monkeys distort probability in a manner similar to humans. Therefore, we investigated economic choices in macaque monkeys for evidence of probability distortion. We trained two monkeys to predict reward from probabilistic gambles with constant outcome values (0.5 ml or nothing). The probability of winning was conveyed using explicit visual cues (sector stimuli). Choices between the gambles revealed that the monkeys used the explicit probability information to make meaningful decisions. Using these cues, we measured probability distortion from choices between the gambles and safe rewards. Parametric modeling of the choices revealed classic probability weighting functions with inverted-S shape. Therefore, the animals overweighted low probability rewards and underweighted high probability rewards. Empirical investigation of the behavior verified that the choices were best explained by a combination of nonlinear value and nonlinear probability distortion. Together, these results suggest that probability distortion may reflect evolutionarily preserved neuronal processing. Copyright © 2015 Stauffer et al.

COVAL, Compound Probability Distribution for Function of Probability Distribution

International Nuclear Information System (INIS)

Astolfi, M.; Elbaz, J.

1979-01-01

1 - Nature of the physical problem solved: Computation of the probability distribution of a function of variables, given the probability distribution of the variables themselves. 'COVAL' has been applied to reliability analysis of a structure subject to random loads. 2 - Method of solution: Numerical transformation of probability distributions

APPROXIMATION OF PROBABILITY DISTRIBUTIONS IN QUEUEING MODELS

Directory of Open Access Journals (Sweden)

T. I. Aliev

2013-03-01

Full Text Available For probability distributions with variation coefficient, not equal to unity, mathematical dependences for approximating distributions on the basis of first two moments are derived by making use of multi exponential distributions. It is proposed to approximate distributions with coefficient of variation less than unity by using hypoexponential distribution, which makes it possible to generate random variables with coefficient of variation, taking any value in a range (0; 1, as opposed to Erlang distribution, having only discrete values of coefficient of variation.

Cladding failure probability modeling for risk evaluations of fast reactors

International Nuclear Information System (INIS)

Mueller, C.J.; Kramer, J.M.

1987-01-01

This paper develops the methodology to incorporate cladding failure data and associated modeling into risk evaluations of liquid metal-cooled fast reactors (LMRs). Current U.S. innovative designs for metal-fueled pool-type LMRs take advantage of inherent reactivity feedback mechanisms to limit reactor temperature increases in response to classic anticipated-transient-without-scram (ATWS) initiators. Final shutdown without reliance on engineered safety features can then be accomplished if sufficient time is available for operator intervention to terminate fission power production and/or provide auxiliary cooling prior to significant core disruption. Coherent cladding failure under the sustained elevated temperatures of ATWS events serves as one indicator of core disruption. In this paper we combine uncertainties in cladding failure data with uncertainties in calculations of ATWS cladding temperature conditions to calculate probabilities of cladding failure as a function of the time for accident recovery. (orig.)

Improved process for calculating the probability of being hit by crashing aircraft by the Balfanz-model

International Nuclear Information System (INIS)

Hennings, W.

1988-01-01

For calculating the probability of being hit by crashing military aircraft on different buildings, a model was introduced, which has already been used in the conventional fields. In the context of converting the research reactor BER II, this model was also used in the nuclear field. The report introduces this model and shows the application to a vertical cylinder as an example. Compared to the previous model, an exact and also simpler solution of the model attempt for determining the shade surface for different shapes of buildings is derived. The problems of the distribution of crashes given by the previous model is treated via the vertical angle and an attempt to solve these problems is given. (orig./HP) [de

Quantitative non-monotonic modeling of economic uncertainty by probability and possibility distributions

DEFF Research Database (Denmark)

Schjær-Jacobsen, Hans

2012-01-01

uncertainty can be calculated. The possibility approach is particular well suited for representation of uncertainty of a non-statistical nature due to lack of knowledge and requires less information than the probability approach. Based on the kind of uncertainty and knowledge present, these aspects...... to the understanding of similarities and differences of the two approaches as well as practical applications. The probability approach offers a good framework for representation of randomness and variability. Once the probability distributions of uncertain parameters and their correlations are known the resulting...... are thoroughly discussed in the case of rectangular representation of uncertainty by the uniform probability distribution and the interval, respectively. Also triangular representations are dealt with and compared. Calculation of monotonic as well as non-monotonic functions of variables represented...

The transition probability and the probability for the left-most particle's position of the q-totally asymmetric zero range process

Energy Technology Data Exchange (ETDEWEB)

Korhonen, Marko [Department of Mathematics and Statistics, University of Helsinki, FIN-00014 (Finland); Lee, Eunghyun [Centre de Recherches Mathématiques (CRM), Université de Montréal, Quebec H3C 3J7 (Canada)

2014-01-15

We treat the N-particle zero range process whose jumping rates satisfy a certain condition. This condition is required to use the Bethe ansatz and the resulting model is the q-boson model by Sasamoto and Wadati [“Exact results for one-dimensional totally asymmetric diffusion models,” J. Phys. A 31, 6057–6071 (1998)] or the q-totally asymmetric zero range process (TAZRP) by Borodin and Corwin [“Macdonald processes,” Probab. Theory Relat. Fields (to be published)]. We find the explicit formula of the transition probability of the q-TAZRP via the Bethe ansatz. By using the transition probability we find the probability distribution of the left-most particle's position at time t. To find the probability for the left-most particle's position we find a new identity corresponding to identity for the asymmetric simple exclusion process by Tracy and Widom [“Integral formulas for the asymmetric simple exclusion process,” Commun. Math. Phys. 279, 815–844 (2008)]. For the initial state that all particles occupy a single site, the probability distribution of the left-most particle's position at time t is represented by the contour integral of a determinant.

Building a Model Using Bayesian Network for Assessment of Posterior Probabilities of Falling From Height at Workplaces

Directory of Open Access Journals (Sweden)

Seyed Shamseddin Alizadeh

2014-12-01

Full Text Available Background: Falls from height are one of the main causes of fatal occupational injuries. The objective of this study was to present a model for estimating occurrence probability of falling from height. Methods: In order to make a list of factors affecting falls, we used four expert group's judgment, literature review and an available database. Then the validity and reliability of designed questionnaire were determined and Bayesian networks were built. The built network, nodes and curves were quantified. For network sensitivity analysis, four types of analysis carried out. Results: A Bayesian network for assessment of posterior probabilities of falling from height proposed. The presented Bayesian network model shows the interrelationships among 37 causes affecting the falling from height and can calculate its posterior probabilities. The most important factors affecting falling were Non-compliance with safety instructions for work at height (0.127, Lack of safety equipment for work at height (0.094 and Lack of safety instructions for work at height (0.071 respectively. Conclusion: The proposed Bayesian network used to determine how different causes could affect the falling from height at work. The findings of this study can be used to decide on the falling accident prevention programs.

Joint Probability-Based Neuronal Spike Train Classification

Directory of Open Access Journals (Sweden)

Yan Chen

2009-01-01

Full Text Available Neuronal spike trains are used by the nervous system to encode and transmit information. Euclidean distance-based methods (EDBMs have been applied to quantify the similarity between temporally-discretized spike trains and model responses. In this study, using the same discretization procedure, we developed and applied a joint probability-based method (JPBM to classify individual spike trains of slowly adapting pulmonary stretch receptors (SARs. The activity of individual SARs was recorded in anaesthetized, paralysed adult male rabbits, which were artificially-ventilated at constant rate and one of three different volumes. Two-thirds of the responses to the 600 stimuli presented at each volume were used to construct three response models (one for each stimulus volume consisting of a series of time bins, each with spike probabilities. The remaining one-third of the responses where used as test responses to be classified into one of the three model responses. This was done by computing the joint probability of observing the same series of events (spikes or no spikes, dictated by the test response in a given model and determining which probability of the three was highest. The JPBM generally produced better classification accuracy than the EDBM, and both performed well above chance. Both methods were similarly affected by variations in discretization parameters, response epoch duration, and two different response alignment strategies. Increasing bin widths increased classification accuracy, which also improved with increased observation time, but primarily during periods of increasing lung inflation. Thus, the JPBM is a simple and effective method performing spike train classification.

Reliability of structures by using probability and fatigue theories

International Nuclear Information System (INIS)

Lee, Ouk Sub; Kim, Dong Hyeok; Park, Yeon Chang

2008-01-01

Methodologies to calculate failure probability and to estimate the reliability of fatigue loaded structures are developed. The applicability of the methodologies is evaluated with the help of the fatigue crack growth models suggested by Paris and Walker. The probability theories such as the FORM (first order reliability method), the SORM (second order reliability method) and the MCS (Monte Carlo simulation) are utilized. It is found that the failure probability decreases with the increase of the design fatigue life and the applied minimum stress, the decrease of the initial edge crack size, the applied maximum stress and the slope of Paris equation. Furthermore, according to the sensitivity analysis of random variables, the slope of Pairs equation affects the failure probability dominantly among other random variables in the Paris and the Walker models

Probability of identification: a statistical model for the validation of qualitative botanical identification methods.

Science.gov (United States)

LaBudde, Robert A; Harnly, James M

2012-01-01

A qualitative botanical identification method (BIM) is an analytical procedure that returns a binary result (1 = Identified, 0 = Not Identified). A BIM may be used by a buyer, manufacturer, or regulator to determine whether a botanical material being tested is the same as the target (desired) material, or whether it contains excessive nontarget (undesirable) material. The report describes the development and validation of studies for a BIM based on the proportion of replicates identified, or probability of identification (POI), as the basic observed statistic. The statistical procedures proposed for data analysis follow closely those of the probability of detection, and harmonize the statistical concepts and parameters between quantitative and qualitative method validation. Use of POI statistics also harmonizes statistical concepts for botanical, microbiological, toxin, and other analyte identification methods that produce binary results. The POI statistical model provides a tool for graphical representation of response curves for qualitative methods, reporting of descriptive statistics, and application of performance requirements. Single collaborator and multicollaborative study examples are given.

Development of a statistical model for the determination of the probability of riverbank erosion in a Meditteranean river basin

Science.gov (United States)

Varouchakis, Emmanouil; Kourgialas, Nektarios; Karatzas, George; Giannakis, Georgios; Lilli, Maria; Nikolaidis, Nikolaos

2014-05-01

Riverbank erosion affects the river morphology and the local habitat and results in riparian land loss, damage to property and infrastructures, ultimately weakening flood defences. An important issue concerning riverbank erosion is the identification of the areas vulnerable to erosion, as it allows for predicting changes and assists with stream management and restoration. One way to predict the vulnerable to erosion areas is to determine the erosion probability by identifying the underlying relations between riverbank erosion and the geomorphological and/or hydrological variables that prevent or stimulate erosion. A statistical model for evaluating the probability of erosion based on a series of independent local variables and by using logistic regression is developed in this work. The main variables affecting erosion are vegetation index (stability), the presence or absence of meanders, bank material (classification), stream power, bank height, river bank slope, riverbed slope, cross section width and water velocities (Luppi et al. 2009). In statistics, logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable, e.g. binary response, based on one or more predictor variables (continuous or categorical). The probabilities of the possible outcomes are modelled as a function of independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. 1 = "presence of erosion" and 0 = "no erosion") for any value of the independent variables. The regression coefficients are estimated by using maximum likelihood estimation. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding

DECOFF Probabilities of Failed Operations

DEFF Research Database (Denmark)

Gintautas, Tomas

2015-01-01

A statistical procedure of estimation of Probabilities of Failed Operations is described and exemplified using ECMWF weather forecasts and SIMO output from Rotor Lift test case models. Also safety factor influence is investigated. DECOFF statistical method is benchmarked against standard Alpha-factor...

Single, Complete, Probability Spaces Consistent With EPR-Bohm-Bell Experimental Data

Science.gov (United States)

Avis, David; Fischer, Paul; Hilbert, Astrid; Khrennikov, Andrei

2009-03-01

We show that paradoxical consequences of violations of Bell's inequality are induced by the use of an unsuitable probabilistic description for the EPR-Bohm-Bell experiment. The conventional description (due to Bell) is based on a combination of statistical data collected for different settings of polarization beam splitters (PBSs). In fact, such data consists of some conditional probabilities which only partially define a probability space. Ignoring this conditioning leads to apparent contradictions in the classical probabilistic model (due to Kolmogorov). We show how to make a completely consistent probabilistic model by taking into account the probabilities of selecting the settings of the PBSs. Our model matches both the experimental data and is consistent with classical probability theory.

Sensitivity of probability-of-failure estimates with respect to probability of detection curve parameters

Energy Technology Data Exchange (ETDEWEB)

Garza, J. [University of Texas at San Antonio, Mechanical Engineering, 1 UTSA circle, EB 3.04.50, San Antonio, TX 78249 (United States); Millwater, H., E-mail: harry.millwater@utsa.edu [University of Texas at San Antonio, Mechanical Engineering, 1 UTSA circle, EB 3.04.50, San Antonio, TX 78249 (United States)

2012-04-15

A methodology has been developed and demonstrated that can be used to compute the sensitivity of the probability-of-failure (POF) with respect to the parameters of inspection processes that are simulated using probability of detection (POD) curves. The formulation is such that the probabilistic sensitivities can be obtained at negligible cost using sampling methods by reusing the samples used to compute the POF. As a result, the methodology can be implemented for negligible cost in a post-processing non-intrusive manner thereby facilitating implementation with existing or commercial codes. The formulation is generic and not limited to any specific random variables, fracture mechanics formulation, or any specific POD curve as long as the POD is modeled parametrically. Sensitivity estimates for the cases of different POD curves at multiple inspections, and the same POD curves at multiple inspections have been derived. Several numerical examples are presented and show excellent agreement with finite difference estimates with significant computational savings. - Highlights: Black-Right-Pointing-Pointer Sensitivity of the probability-of-failure with respect to the probability-of-detection curve. Black-Right-Pointing-Pointer The sensitivities are computed with negligible cost using Monte Carlo sampling. Black-Right-Pointing-Pointer The change in the POF due to a change in the POD curve parameters can be easily estimated.

Sensitivity of probability-of-failure estimates with respect to probability of detection curve parameters

International Nuclear Information System (INIS)

Garza, J.; Millwater, H.

2012-01-01

A methodology has been developed and demonstrated that can be used to compute the sensitivity of the probability-of-failure (POF) with respect to the parameters of inspection processes that are simulated using probability of detection (POD) curves. The formulation is such that the probabilistic sensitivities can be obtained at negligible cost using sampling methods by reusing the samples used to compute the POF. As a result, the methodology can be implemented for negligible cost in a post-processing non-intrusive manner thereby facilitating implementation with existing or commercial codes. The formulation is generic and not limited to any specific random variables, fracture mechanics formulation, or any specific POD curve as long as the POD is modeled parametrically. Sensitivity estimates for the cases of different POD curves at multiple inspections, and the same POD curves at multiple inspections have been derived. Several numerical examples are presented and show excellent agreement with finite difference estimates with significant computational savings. - Highlights: ► Sensitivity of the probability-of-failure with respect to the probability-of-detection curve. ►The sensitivities are computed with negligible cost using Monte Carlo sampling. ► The change in the POF due to a change in the POD curve parameters can be easily estimated.

Probability, statistics, and computational science.

Science.gov (United States)