Background: This study aimed to examine the number of latent classes of criminal intent that exist among prisoners and to look at the associations with recidivism, number of police arrests, type of offending (robbery, violent offences, murder, and multiple offences), and age. Participants and Procedure: Latent class analysis was used to identify homogeneous subgroups of prisoners based on their...

In a variety of research domains, data are generated as a consequence of the count process and may possess an ‘excess’ of zeros. There have been many attempts to analyse such data using different statistical methods, including the zero-inflated Poisson (ZiP) and zero-inflated binomial (ZiB) models. The interpretation of these models is however problematic if the covariates considered for the no...

Consider a category of product variants distinguished by some attribute such as color or flavor. A retailer must construct an assortment for the category, i.e., select a subset variants to stock and determine purchase quantities for each offered variant. We analyze this problem using a multinomial logit model to describe the consumer choice process and a newsboy model to represent the retailer’...

The paper aims to find an efficient model for consumer credit scoring using neural networks in comparison with logistic regression. A specific characteristic of the examined data set was that the credit repayment period was not completed. Applicants are divided into three categories: "good", "bad", and indeterminate ("poor") applicants which influenced the model accuracy. Five different modelin...

In this paper, we proposed an adaptive robust variable selection procedure for the logistic regression model. The method is to outliers and considers goodness-of-fit of Furthermore, apply MM algorithm solve optimization problem. Monte Carlo studies are evaluated finite-sample performance method. results show that when there in dataset or distribution covariate deviates from normal distribution,...

in this study, an effort has been made to determine the most important risk factors of tuberculosis (tb) in district mardan. a total of 645 cases were examined, and their personal and medical data were collected. for each case, the phenomenon of tb was studied in relation to different risk factors. statistical techniques of logistic regression and backward elimination procedure were used to ana...

This paper describes about the performance analysis of different data mining classifiers before and after feature selection on binomial data set. Three data mining classifiers Logistic Regression, SVM and Neural Network classifiers are considered in this paper for classification. The Congressional Voting Records data set is a binomial data set investigated in this study is taken from UCI machin...