Research in statistics covers Robust Statistics, Extreme Value Theory, Bayesian Modelling and Inference, Multivariate Analysis, Survival Analysis and Time Series.  The main focus of research on Robust Statistics deals with robust diagnostic methods and robust parameters estimation in linear, nonlinear, logistic, generalized linear and response surface models, when data is contaminated with outliers.  Robust Variable Selection Procedure, Robust Statistical Process Control and Robust Methods on panel data also the research interest in robust statistics. Meanwhile, Extreme Value Theory is used for modelling series of extreme data of observed physical processes. Bayesian Analysis is a statistical procedure in which we combine prior information about a population parameter with evidence from information contained in a sample to guide the statistical inference process. Research in Multivariate Analysis mainly focused on the application of multivariate techniques such as regression modelling, discriminant analysis, principal components, factor analysis, cluster analysis, structural modelling and etc. Survival Analysis comprises of several methods for analyzing data where the variable is the time until the occurrence of an event and the data is usually incomplete or censored. Time Series Modelling is useful for forecasting various phenomena, whereas spatial modelling refers to modelling random phenomena on a two dimensional finite plane.

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• Doctor of Philosophy (Statistics)
• Statistics
• Doctor of Philosophy