On the detection of changes in autoregressive time series I. Asymptotics (original) (raw)

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A method for detecting changes in long time series

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Testing for Shifts in Trend With an Integrated or Stationary Noise Component

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A Powerful Portmanteau Test of Lack of Fit for Time Series

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An Improved Method of Sequential Probability Ratio Test for Change Point Detection in Time Series

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Monitoring procedure for parameter change in causal time series

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Testing for Trend in the Presence of Autoregressive Error: A Comment

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Hypothesis testing for some time-series models: a power comparison

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Test for Parameter Change in ARIMA Models

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On testing for independence between the innovations of several time series

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Inference for parameter instability in time series via trending regression

Marie Husková

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Testing for Trend in the Presence of Autoregressive Error

Pierre Perron

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Testing for Cyclical Non‐Stationarity in Autoregressive Processes

Robert Kunst

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Bootstrapping confidence intervals for the change-point of time series

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Evaluation of linear trend tests using resampling techniques

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Bootstrap in Detection of Changes in Linear Regression

J. Picek, Marie Husková

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Exact simulation-based inference for autoregressive processes based on induced tests∗

Malika Neifar

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Detecting exponential component in autoregressive models: comparative study between several tests of nonlinearity

SAID EL MELHAOUI

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A point optimal test for autoregressive disturbances

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Evaluation of surrogate and bootstrap tests for nonlinearity in time series

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Estimation and hypothesis testing in nonstationary time series

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Testing for smooth structural changes in time series models via nonparametric regression

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On a robust test for SETAR-type nonlinearity in time series analysis

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