Tsukasa Hokimoto

University of Tokyo Japan

Tsukasa Hokimoto is an associate professor of Statistical Science and Data Science at Hokkaido Information University, Japan. His main research interests include the development of statistical methodologies for data analysis and their application to the analysis of natural phenomena in the fields of oceanography, meteorology, and biology. His recent research includes developing statistical models for characterizing directional time series data, based on the theory of nonhomogeneous hidden Markov models.

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In recent years, statistical techniques and methods for data analysis have advanced significantly in a wide range of research areas. These developments enable researchers to analyze increasingly large datasets with more flexibility and also more accurately estimate and evaluate the phenomena they study. We recognize the value of recent advances in data analysis techniques in many different research fields. However, we also note that awareness of these different statistical and probabilistic approaches may vary, owing to differences in the datasets typical of different research fields. This book provides a cross-disciplinary forum for exploring the variety of new data analysis techniques emerging from different fields.

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