Indirect inference for locally stationary ARMA processes with stable innovations-Reference-Cited by-同舟云学术

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Indirect inference for locally stationary ARMA processes with stable innovations

Published:2020-07-27 Issue:17 Volume:90 Page:3106-3134
ISSN:0094-9655
Container-title:Journal of Statistical Computation and Simulation
language:en
Short-container-title:Journal of Statistical Computation and Simulation

Author:

Chou-Chen Shu Wei¹^ORCID,Morettin Pedro A.¹^ORCID

Affiliation:

1. Institute of Mathematics and Statistics, University of São Paulo, São Paulo, Brazil

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnol ogico

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Informa UK Limited

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Link

https://www.tandfonline.com/doi/pdf/10.1080/00949655.2020.1797030

Reference28 articles.

1. Maximum likelihood estimation and model selection for locally stationary processes∗

2. Fitting time series models to nonstationary processes

3. Dahlhaus R. Locally stationary processes. In: Tata Subba Rao SSR, Rao C, editors. Time series analysis: methods and applications. (Handbook of Statistics; vol. 30). North Holland. Elsevier; 2012. p. 351–413.

4. Simple consistent estimators of stable distribution parameters

5. An iterative procedure for the estimation of the parameters of stable laws

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A two-step estimation procedure for locally stationary ARMA processes with tempered stable innovations;Brazilian Journal of Probability and Statistics;2023-03-01

2. Unsupervised Change Point Detection and Trend Prediction for Financial Time-Series Using a New CUSUM-Based Approach;IEEE Access;2022

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