Titlebook: Change Point Analysis for Time Series; Lajos Horváth,Gregory Rice Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusi

只看該作者 · 發(fā)表于 2025-3-23 10:57:55

https://doi.org/10.1007/978-981-16-2442-1ich the goal is to conduct change point analysis retrospectively on an observed series. In this chapter, we shift our focus to sequential or “online” change point detection methods. These aim to detect a change point in the data generating process, relative to a stable training or historical sample,

只看該作者 · 發(fā)表于 2025-3-23 14:31:56

https://doi.org/10.1007/978-981-16-2442-1we change our notation slightly to denote such multivariate time series data as . where we think of . and . as denoting “time”, and . denotes the dimension or number of “cross-sectional units” that we observe. For example, such data might comprise real valued observations of . financial or economic

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只看該作者 · 發(fā)表于 2025-3-23 23:24:11

Change Point Analysis for Time Series978-3-031-51609-2Series ISSN 0172-7397 Series E-ISSN 2197-568X

只看該作者 · 發(fā)表于 2025-3-24 02:31:40

只看該作者 · 發(fā)表于 2025-3-24 08:42:05

https://doi.org/10.1007/978-981-16-2442-1we change our notation slightly to denote such multivariate time series data as . where we think of . and . as denoting “time”, and . denotes the dimension or number of “cross-sectional units” that we observe. For example, such data might comprise real valued observations of . financial or economic time series over . time units.

只看該作者 · 發(fā)表于 2025-3-24 13:58:48

只看該作者 · 發(fā)表于 2025-3-24 17:35:32

High-Dimensional and Panel Data,we change our notation slightly to denote such multivariate time series data as . where we think of . and . as denoting “time”, and . denotes the dimension or number of “cross-sectional units” that we observe. For example, such data might comprise real valued observations of . financial or economic time series over . time units.

只看該作者 · 發(fā)表于 2025-3-24 19:31:07

Book 2024r models. The book primarily focuses on asymptotic theory and practical applications of change point analysis. The methods discussed in the book go beyond the traditional change point methods for univariate and multivariate series. It also explores techniques for handling heteroscedastic series, hig

只看該作者 · 發(fā)表于 2025-3-25 03:13:12

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