Sebastian George

• Doctor of Philosophy
• Professor (Associate) at Kannur University

The study of stress-strength reliability estimation based on phase-type distribution helps to gather results on estimation of stress-strength reliability with any probability distribution that is defined on the non negative real numbers as any discrete or continuous probability distributions on the positive real line can be represented as phase-ty...

Objectives: In medical research, the design of a study and the statistical methods are important since these direct the interpretation and conclusion. The selection of appropriate statistical models depends on the distribution of the outcome measure. Count data are commonly used in medical research, but are often over-dispersed or zero inflated. In...

In case-control studies, odds ratios (OR) are calculated from 2 × 2 tables and in some instances, we observe small cell counts or zero counts in one of the cells. The corrections to calculate the ORs in the presence of empty cells are available in literature. Some of these include Yates continuity correction and Agresti and Coull correction. Howeve...

Stress-strength modeling has achieved considerable attention in recent years due to its applicability in various areas like engineering, quality control, psychology, biology, genetics, medicine etc. Phase-type distribution is a generalized class of distributions that is closed under several mathematical operations like maxima, minima, convolution,...

Background While dealing with skewed outcome, researchers often use log-transformation to convert the data into normal and apply commonly used statistical tests like t-test, linear regression, etc. However, the log-transformed data will not be normal at all times. In such situations, Box-Cox transformation (BCT) can be used to transform skewed data...

Background Count data represents the number of occurrences of an event within a fixed period of time.In count data modelling, overdispersion is inevitable. Sometimes, this overdispersion may not be just due to the excess zeros but may be due to the presence of two or more mixtures. Hence the main objective is to examine for the presence of mixtures...

The most suitable statistical method for explaining serial dependency in time series count data is that based on Hidden Markov Models (HMMs). These models assume that the observations are generated from a finite mixture of distributions governed by the principle of Markov chain (MC). Poisson-Hidden Markov Model (P-HMM) may be the most widely used m...

The use of the harmonic regression model is well accepted in the epidemiological and biostatistical communities as a standard procedure to examine seasonal patterns in disease occurrence. While these models may provide good fit to periodic patterns with relatively symmetric rises and falls, for some diseases the incidence fluctuates in a more compl...

Hidden Markov models are stochastic models in which the observations are assumed to follow a mixture distribution, but the parameters of the components are governed by a Markov chain which is unobservable. The issues related to the estimation of Poisson-hidden Markov models in which the observations are coming from mixture of Poisson distributions...

Diarrheal disease is one among the top five causes of death in low- and middle-income countries. It is the second leading cause of death in children under five years of age. Diarrheal disease contributes to the mortality of nearly 1.5 million children and globally there are about two billion cases of diarrheal diseases every year. In the present st...

Microarrays allow the study of the expression profile of hundreds to thousands of genes simultaneously. These expressions could be from treated samples and the healthy controls. The Esscher transformed Laplace distribution is used to fit microarray expression data as compared to Normal and Laplace distributions. The Maximum Likelihood Estimation pr...

Background and Objective: In the analysis of dichotomous type response variable, logistic regression is usually used. However, the performance of logistic regression in the presence of sparse data is questionable. In such a situation, a common problem is the presence of high odds ratios (ORs) with very wide 95% confidence interval (CI) (OR: >999.99...

Auto-regressive Condition Poisson(ACP) modelling of time series data.

When faced with the problem of comparing positively skewed outcome values, data transformations such as log and square root etc, are often used. However, this approach suffers with the difficulty in interpretability, lack of accuracy etc. That is, while the back transformation of mean is possible, but not for the standard deviation. This paper pres...

In this article we consider a class of asymmetric distributions which belongs to one parameter regular exponential family. The Marshall–Olkin version of this family is also considered. Various properties are examined. Applications of these models in time series analysis are discussed. We also consider an application of Marshall–Olkin Esscher transf...

In the present paper, the asymmetric type II compound Laplace distribution is introduced and various properties are studied. The maximum likelihood estimation procedure is employed to estimate the parameters of the proposed distribution and an algorithm in R package is developed to carry out the estimation. Simulation studies for various choices of...

Heavy-tailed distributions have wide applications in life-time contexts, especially in reliability and risk modeling. So we consider the estimation problem of reliability, R=P (X >Y ) , when X and Y are two independent but not identically distributed random variables belonging to the family of heavy-tailed distributions, using a robust estimator, n...

In this paper we present a method useful for the system engineer to improve the service performance of a Web server through session-based Web workload, the best indicator of the users perception of the Web quality. Bytes transferred per session is one of the characteristics of intra-session which collectively describe session-based Web workload. Th...

In this article, we introduce an alternative distribution, namely Esscher transformed Laplace distribution good enough to model the fle size distribution of Web servers. It exhibits asymmetry, peakedness and tail heaviness, which are common features of fle size data. Esscher transformed Laplace distribution belongs to one parameter regular exponent...

In this paper we present a new family of univariate slash distributions, which arises as the ratio of logistic distribution and independent uniform power function distribution. Slash logistic and skew Slash logistic distributions were derived and the properties were studied. Logistic and skew logistic distributions are special cases of this new fam...

Dirichlet integrals and the associated Dirichlet statistical densities are widely used in various areas. Generalizations of Dirichlet integrals and Dirichlet models to matrix-variate cases, when the matrices are real symmetric positive definite or hermitian positive definite, are available \cite{4}. Real scalar variables case of the Dirichlet model...