The Cusum Test for Parameter Change in Time Series Models

By Sangyeol Lee, Jeongcheol Ha, Okyoung Na, Seongryong Na. 2003

237 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/34bd52ca8e3293d845f7dc63a38e5244210e9da8

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In Control and Systems Engineering

In Statistics and Probability

Citations in the corpus

Parameter Change Test for Poisson Autoregressive Models (2014, methodology): “As seen in Lee et al. (2003), the functional limit theorem for martingales is a key tool to verify the asymptotic results for the CUSUM test, say, I. 0/ 1=2 1p n @LŒns .”
Detection of Multiple Structural Breaks in Multivariate Time Series (2013, methodology): “As with all methods in this context (see, e.g., Lee et al. 2003), the new procedure depends on the choice of several regularization parameters.”
The Cusum Test for Parameter Change in Regression Models with ARCH Errors (2004, methodology): “Despite the previous work of Lee et al. (2003b) also considers a residual cusum test in time series models, the model of main concern was the autoregressive model with several unit roots. In fact, the mathematical analysis of the cusum test heavily relies on the probabilistic structure of the underl”
THE LIMIT DISTRIBUTION OF THE CUSUM OF SQUARES TEST UNDER GENERAL MIXING CONDITIONS (2008, background): “…its limit distribution when the data are assumed to follow a zero mean linear process ~a similar result in a more general setup is presented in Lee, Ha, and Na, 2003!+ Koksozka and Leipus ~2000! dealt with a zero mean series with autoregressive conditionally heteroskedastic ~ARCH! errors and…”
Validating Stationarity Assumptions in Time Series Analysis by Rolling Local Periodograms (2010, methodology): “We next investigate the power behavior of the testing procedure proposed and compare its performance to that of a CUSUM type test for detecting changes in the autocovariance structure; cf. Lee et al. (2003).”
Parameter change test for random coefficient integer‐valued autoregressive processes with application to polio data analysis (2009, methodology): “Recently, Lee et al. (2003) demonstrated that the CUSUM test can be used in various time-series models.”