Research Papers in Statistical Inference for Time Series and Related Models: Essays in Honor of Masanobu Taniguchi by Yan Liu, Junichi Hirukawa, Yoshihide Kakizawa
English | PDF (True) | 2023 | 591 Pages | ISBN : 9819908027 | 24.4 MB
This book compiles theoretical developments on statistical inference for time series and related models in honor of Masanobu Taniguchi's 70th birthday. It covers models such as long-range dependence models, nonlinear conditionally heteroscedastic time series, locally stationary processes, integer-valued time series, Lévy Processes, complex-valued time series, categorical time series, exclusive topic models, and copula models. Many cutting-edge methods such as empirical likelihood methods, quantile regression, portmanteau tests, rank-based inference, change-point detection, testing for the goodness-of-fit, higher-order asymptotic expansion, minimum contrast estimation, optimal transportation, and topological methods are proposed, considered, or applied to complex data based on the statistical inference for stochastic processes.