Listed in alphabetical order according to the last name of the speaker Robust Estimation of the Change Point in the Simple Linear Regression Model: JFST Error Distribution S. Acitas, B. Senoglu, and O. Arslan 1 Department of Statistics, Anadolu University, Eskisehir, Turkey 2 Department of Statistics, Ankara University, Ankara, Turkey

Introduction IBM SPSS Statistics Server is robust, powerful analytical software that seamlessly scales from handling the analytical needs of a single department to hundreds of users across the enterprise. It provides all of the features of IBM SPSS Statistics, plus capabilities that deliver faster performance, more efficient processing of large datasets and enhanced security in enterprise deplo...

Summary Information from multiple data sources is increasingly available. However, some may produce biased estimates due to sampling, corruption or model misspecification. Thus there a need for robust combination methods that can be used with sources. In this paper, fusion-extraction method proposed. Unlike existing methods, the proposed applied in important case where researchers have no knowl...

The family of density power divergences is an useful class which generates robust parameter estimates with high efficiency. None of these divergences require any non-parametric density estimate to carry out the inference procedure. However, these divergences have so far not been used effectively in robust testing of hypotheses. In this paper, we develop tests of hypotheses based on this family ...