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Related papers: New Goodness-of-Fit Tests for Time Series Models

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Autoregressive and moving-average (ARMA) models with stable Paretian errors is one of the most studied models for time series with infinite variance. Estimation methods for these models have been studied by many researchers but the problem…

Statistics Theory · Mathematics 2016-11-07 Jen-Wen Lin , A. Ian McLeod

A new portmanteau test statistic is proposed for detecting nonlinearity in time series data. In this paper, we elaborate on the Toeplitz autocorrelation matrix to the autocorrelation and cross-correlation of residuals and squared residuals…

Statistics Theory · Mathematics 2022-09-01 Esam Mahdi , Thomas J. Fisher

This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time series process, including those exhibiting long-range dependence. Test statistics for composite hypotheses are functionals of a (approximated)…

Statistics Theory · Mathematics 2007-06-13 Miguel A. Delgado , Javier Hidalgo , Carlos Velasco

This paper studies the model selection problem in a large class of causal time series models, which includes both the ARMA or AR($\infty$) processes, as well as the GARCH or ARCH($\infty$), APARCH, ARMA-GARCH and many others processes. To…

Statistics Theory · Mathematics 2019-07-24 Jean-Marc Bardet , Kare Kamila , William Kengne

We propose an empirical likelihood test that is able to test the goodness of fit of a class of parametric and semi-parametric multiresponse regression models. The class includes as special cases fully parametric models; semi-parametric…

Statistics Theory · Mathematics 2010-01-12 Song Xi Chen , Ingrid Van Keilegom

Using cumulative residual processes, we propose joint goodness-of-fit tests for conditional means and variances functions in the context of nonlinear time series with martingale difference innovations. The main challenge comes from the fact…

Methodology · Statistics 2021-07-02 Kilani Ghoudi , Naâmane Laïb , Mohamed Chaouch

Assessing model adequacy is a crucial step in regression analysis, ensuring the validity of statistical inferences. For Generalized Functional Linear Models (GFLMs), which are widely used for modeling relationships between scalar responses…

Methodology · Statistics 2025-11-14 Feifei Chen , Kaiming Zhang , Yanni Zhang , Hua Liang

We propose a family of tests to assess the goodness-of-fit of a high-dimensional generalized linear model. Our framework is flexible and may be used to construct an omnibus test or directed against testing specific non-linearities and…

Methodology · Statistics 2019-11-14 Jana Janková , Rajen D. Shah , Peter Bühlmann , Richard J. Samworth

We study goodness-of-fit testing for non-causal autoregressive time series with non-Gaussian stable noise. To model time series exhibiting sharp spikes or occasional bursts of outlying observations, the exponent of the non-Gaussian stable…

Statistics Theory · Mathematics 2012-09-19 Yunwei Cui , Rongning Wu , Thomas J. Fisher

It is an important task in the literature to check whether a fitted autoregressive moving average (ARMA) model is adequate, while the currently used tests may suffer from the size distortion problem when the underlying autoregressive models…

Methodology · Statistics 2022-09-21 Xiaohui Liu , Donghui Fan , Xu Zhang , Catherine C. Liu

The problem of test of fit for Vector AutoRegressive (VAR) processes with unconditionally heteroscedastic errors is studied. The volatility structure is deterministic but time-varying and allows for changes that are commonly observed in…

Methodology · Statistics 2015-03-19 Valentin Patilea , Hamdi Raïssi

This paper introduces a novel goodness-of-fit test technique for parametric conditional distributions. The proposed tests are based on a residual marked empirical process, for which we develop a conditional Principal Component Analysis. The…

Econometrics · Economics 2025-06-18 Cui Rui , Li Yuhao

In this paper we present the results from an empirical power comparison of 40 goodness-of-fit tests for the univariate Laplace distribution, carried out using Monte Carlo simulations with sample sizes $n = 20, 50, 100, 200$, significance…

Methodology · Statistics 2023-01-02 Alain Desgagné , Pierre Lafaye de Micheaux , Frédéric Ouimet

It is now widely accepted that, to model the dynamics of daily financial returns, volatility models have to incorporate the so-called leverage effect. We derive the asymptotic behaviour of the squared residuals autocovariances for the class…

Statistics Theory · Mathematics 2018-11-22 Yacouba Boubacar Maïnassara , Othman Kadmiri , Bruno Saussereau

This paper proposes several tests of restricted specification in nonparametric instrumental regression. Based on series estimators, test statistics are established that allow for tests of the general model against a parametric or…

Econometrics · Economics 2019-09-24 Christoph Breunig

A new portmanteau diagnostic test for vector autoregressive moving average (VARMA) models that is based on the determinant of the standardized multivariate residual autocorrelations is derived. The new test statistic may be considered an…

Statistics Theory · Mathematics 2016-11-03 Esam Mahdi , A. Ian McLeod

Record is used to reduce the time and cost of running experiments (Doostparast and Balakrishnan, 2010). It is important to check the adequacy of models upon which inferences or actions are based (Lawless, 2003, Chapter 10, p. 465). In the…

Statistics Theory · Mathematics 2011-10-26 Mahdi Doostparast

In many statistical modeling frameworks, goodness-of-fit tests are typically administered to the estimated residuals. In the time series setting, whiteness of the residuals is assessed using the sample autocorrelation function. For many…

Statistics Theory · Mathematics 2019-03-05 Phyllis Wan , Richard A. Davis

We establish the asymptotic behaviour of the sum of squared residuals autocovariances and autocorrelations for the class of multi-variate power transformed asymmetric models. We then derive a portmanteau test. We establish the asymptotic…

Statistics Theory · Mathematics 2024-04-22 Yacouba Boubacar Maïnassara , Othman Kadmiri , Bruno Saussereau

Ordinal categorical data are widely collected in psychology, education, and other social sciences, appearing commonly in questionnaires, assessments, and surveys. Latent class models provide a flexible framework for uncovering unobserved…

Machine Learning · Statistics 2026-02-26 Huan Qing
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