S.K. Upadhyay

Carcinoma of the gallbladder: Is it a sequel of typhoid?

Gallbladder diseases, including carcinoma, are common in the northern part of India and so are Salmonella typhi infection and typhoid carrier state. This study was aimed to find out the association of typhoid carrier state in patients with cholelithiasis, carcinoma of the gallbladder, and controls. The three groups are comparable in age and sex composition. This is the first study of its kind from an area of high endemicity for both typhoid infection and carcinoma of the gallbladder. A case–control study was carried out to detect typhoid carrier state among the patients with biliary diseases and healthy controls, using indirect haemagglutination assay measuring antibodies against highly purified S. typhi Vi polysaccharide antigen. A significantly high Vi positivity was observed in patients with gallbladder carcinoma (29.4%) compared to controls (5%) (χ2 = 6.325, P < 0.004, OR = 7.19) and patients with cholelithiasis (10.7%) (χ2 = 5.066, P < 0.01, OR = 3.86). There is 8.47 times more risk of developing carcinoma of the gallbladder in culture-positive typhoid carriers than the noncarriers. The present study suggests the typhoid carrier state to be one of the possible mechanisms of gallbladder carcinogenesis.

Estimation of parameters for exponentiated-Weibull family under type-II censoring scheme

Bayes and classical estimators have been obtained for two-parameter exponentiated-Weibull distribution when sample is available from type-II censoring scheme. Bayes estimators have been developed under squared error loss function as well as under LINEX loss function using non-informative type of priors for the parameters. Besides, the generalized maximum likelihood estimators and the usual maximum likelihood estimators have also been attempted. It has been seen that the estimators obtained are not available in nice closed forms, although they can be easily evaluated for the given sample by using suitable numerical methods. The performance of the proposed estimators have been compared on the basis of their simulated risks (average loss over the sample space) obtained under squared error as well as under LINEX loss functions.

A Bayes analysis of modified Weibull distribution via Markov chain Monte Carlo simulation

This paper presents the posterior analysis of a new family defined in the literature as modified Weibull distribution. This family is a modification of the two-parameter Weibull model in the sense that it, besides covering increasing and decreasing hazard rates, also represents bathtub-shaped behaviour. Both the Gibbs sampler and the Metropolis algorithms have been used to provide complete analysis of the concerned posterior surfaces. The paper also considers examining the issue of model validation using predictive simulation ideas and the Bayesian p-value. Finally, numerical illustration has been provided based on two real data sets.

Weibull extension model: A Bayes study using Markov chain Monte Carlo simulation

Several generalizations of the two-parameter Weibull model have been proposed to model data sets that exhibit complex non-monotone shapes of hazard rate function. The present paper focuses on one such generalization referred to as the Weibull extension model in the literature. Complete Bayesian analysis of the model has been provided using Markov chain Monte Carlo simulation. Finally, a thorough study has been conducted for checking the adequacy of the model for a given data set using some of the graphical and numerical methods based on predictive simulation ideas. A real data set is considered for illustration.

ESTIMATION OF EXPONENTIATED WEIBULL SHAPE PARAMETERS UNDER LINEX LOSS FUNCTION

ABSTRACT The paper deals with Bayes estimation of the exponentiated Weibull shape parameters under linex loss function when independent non-informative type of priors are available for the parameters. Generalized maximum likelihood estimators have also been obtained. Performances of the proposed Bayes estimator, generalized maximum likelihood estimators, posterior mean (i.e., Bayes estimator under squared error loss function) and maximum likelihood estimators have been studied on the basis of their risks under linex loss function. The comparison is based on a simulation study because the expressions for risk functions of these estimators cannot be obtained in nice closed forms.

Estimation of exponential parameters under multiply type II censoring

This article considers a multiply type II censored sample from one parameter exponential distribution. Using a generalized non–informative prior, Bayes estimators of scale parameter and reliability function areproposed. The proposed estimators are compared with their corresponding MLEs and BLUEs on the basis of a Monte Carlo simulation study of 100 samples.

Carrier-mediated transport through liquid membranes Studies on transport of nickel, cadmium and lead ions using tetradentate oxoiminato Schiff base ligands as carriers

Abstract Transport of nickel, cadmium and lead ions through a chloroform liquid membrane containing four new tetradentate oxoiminato Schiff bases as carriers has been studied. Variation of the rate of transport with the concentration of the metal salts in the source phase and with accompanying anion has been studied. Correlation of rates of transport with the free energies of hydration of the accompanying anions has been investigated.

Choice Between Weibull and Lognormal Models: A Simulation Based Bayesian Study

Abstract The Weibull and the lognormal distributions are the most widely used models for analyzing a variety of data from different fields. It is often seen that the two models quite nicely represent a given data set although the concerned analyses and the related inferential procedures may differ drastically. It is, therefore, highly desirable to study the behavior of the two models for a given set of observations in the light of recent tool-kits of model comparison/model choice. The article considers examining the issue of choosing the right model through a simulation based Bayesian study using the output from the Gibbs sampler.

Assessing the Value of the Threshold Parameter in the Weibull Distribution Using Bayes Paradigm

The Weibull distribution represents a wide variety of situations. Usually, the distribution is considered as a two-parameter family with a scale, and a shape parameter. If, however, the given data reflect additional information in the form of a minimum guarantee, a positive value away from zero, it is better to go for a three-parameter model with the additional parameter known as the threshold. The threshold parameter is often very important, but increases the complexity of the model. Arbitrarily going for the three-parameter form is not advisable unless it is really required by the data. This article attempts to make a simulation-based Bayesian study for checking if the threshold parameter can be taken to be zero or positive in situations representing the two models. We study the compatibility of the models for the given data set. We conduct the posterior simulation in each case using Gibbs sampling.

Bayes results for classical Pareto distribution via Gibbs sampler, with doubly-censored observations

The paper considers the full Bayes analysis of the Pareto distribution when the observations are doubly censored, and provides sample-based estimates of posterior distributions using Gibbs sampler algorithm. The approach is not only computationally simple but fully explores the low-dimensional posterior surfaces-which otherwise seems difficult. Complexities through censored data always arise in life testing experiments; these complexities are no longer problems with the Gibbs sampler algorithm, unlike the situations with nonsample-based approaches.