The multiple testing problem for Box-Pierce statistics
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Publication:2452104
DOI10.1214/14-EJS892zbMath1349.62418OpenAlexW2081667690MaRDI QIDQ2452104
Tucker S. McElroy, Brian Monsell
Publication date: 30 May 2014
Published in: Electronic Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://projecteuclid.org/euclid.ejs/1399901042
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Paired and multiple comparisons; multiple testing (62J15)
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- A local spectral approach for assessing time series model misspecification
- A central limit theorem for stationary processes and the parameter estimation of linear processes
- Time series: theory and methods.
- Asymptotic theory of statistical inference for time series
- The multiple testing problem for Box-Pierce statistics
- On the distribution of the sample autocorrelation coefficients
- On multiple portmanteau tests
- An Improvement of the Portmanteau Statistic
- On the distribution of positive-definite Gaussian quadratic forms
- Diagnostic testing of univariate time series models
- On a measure of lack of fit in time series models
- A proposal for a residual autocorrelation test in linear models
- Further results on the finite-sample distribution of Monti's portmanteau test for the adequacy of an ARMA (p,q) model
- On the finite-sample distribution of modified portmanteau tests for radomness of a Gaussian time series
- A Powerful Portmanteau Test of Lack of Fit for Time Series
- Two-Sample Repeated Significance Tests Based on the Modified Wilcoxon Statistic
- Statistical Properties of Model-Based Signal Extraction Diagnostic Tests
- Computing the distribution of quadratic forms in normal variables
- Distribution of Residual Autocorrelations in Autoregressive-Integrated Moving Average Time Series Models
- An exponential model for the spectrum of a scalar time series
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