Logistic regression with binary and multinomial outcomes is commonly used, and researchers have long searched for an interpretable measure of the strength of a particular logistic model. This article describes the large sample properties of some pseudo-R statistics for assessing the predictive strength of the logistic regression model. We present theoretical results regarding the convergence an...

Logistic regression is an important statistical analysis methods widely used in research fields, including health, business and government. On the other hand preserving data privacy is a crucial aspect in every information system. Many privacy-preserving protocols have been proposed for different statistical techniques, with various data distributions, owners and users. In this paper, we propos...

Logistic regression is a commonly used representation for aggregators in Bayesian belief networks when a child has multiple parents. In this paper we consider extending logistic regression to relational models, where we want to model varying populations and interactions among parents. In this paper, we first examine the representational problems caused by population variation. We show how these...

We advocate Logistic Regression (LR) as an alternative to the Support Vector Machine (SVM) classifiers commonly used in steganalysis. LR offers more information than traditional SVM methods – it estimates class probabilities as well as providing a simple classification – and can be adapted more easily and efficiently for multiclass problems. Like SVM, LR can be kernelised for nonlinear classifi...

for −∞ < z < ∞. The properties of this distribution and its generalizations have been studied by several authors. Of particular eminence are the numerous papers on this topic by Professor N. Balakrishnan and his colleagues; see, for example, Balakrishnan [1, 2, 3], Balakrishnan and Aggarwala [4], Balakrishnan et al. [5, 7, 12], Balakrishnan and Chan [6], Balakrishnan and Joshi [8], Balakrishnan...

Article history: Received 24 December 2010 Available online 24 December 2011 Communicated by L. Yin

in many industrial and non-industrial applications the quality of a process or product is characterized by a relationship between a response variable and one or more explanatory variables. this relationship is referred to as profile. in the past decade, profile monitoring has been extensively studied under the normal response variable, but it has paid a little attention to the profile with the ...

User modeling in advertising and recommendation has typically focused on myopic predictors of user responses. In this work, we consider the long-term decision problem associated with user interaction. We propose a concise specification of long-term interaction dynamics by combining factored dynamic Bayesian networks with logistic predictors of user responses, allowing state-of-the-art predictio...

A new type of an integrable mapping is presented. This map is equipped with fractional difference and possesses an exact solution, which can be regarded as a discrete analogue of the Mittag-Leffler function.