A common goal in modeling and data mining is to determine, based on sample data,
whether or not a change of some sort has occurred in a quantity of interest. The study of …

In this study, we consider the problem of testing for a parameter change in general integer-
valued time series models whose conditional distribution belongs to the one-parameter …

The analysis of text data using artificial intelligence and statistical methods has become
increasingly important in recent years. One application is the automatic assignment of …

This thesis considers the application of changepoint detection methodology for the analysis
of acoustic sensing signals. In the first part, we propose a detection procedure for changes in …

Change-point detection for categorical data has wide applications in many fields. Existing
methods either are distribution-free, not utilizing categorical information sufficiently, or have …

Divergences (distances), which measure the dissimilarity, respectively, proximity, between
two probability distributions, have turned out to be very useful for several different tasks in …

Parameter change test has been an important issue in time series analysis. The problem
has also been actively explored in the field of integer-valued time series, but the testing in …

This study considers the problem of testing for parameter change, particularly in the
presence of outliers. To lessen the impact of outliers, we propose a robust test based on the …

Time-series data often have an abrupt structure change at an unknown location. This paper
proposes a new statistic to test the existence of a change-point in a multinomial sequence …

This thesis is devoted to time series analysis, in particular, to segmentation of time series
and to discrimination of time series segments. The problem of measuring time series …