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Nonparametric Tests in Linear Model with Autoregressive Errors
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TLDR
In this paper, a family of nonparametric tests for regression under a nuisance autoregression was proposed to avoid the estimation of nuisance parameters, in contrast to the tests proposed in the literature.Abstract:
In the linear regression model with possibly autoregressive errors, we propose a family of nonparametric tests for regression under a nuisance autoregression. The tests avoid the estimation of nuisance parameters, in contrast to the tests proposed in the literature.read more
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Journal ArticleDOI
Time Series: Theory and Methods (2nd ed.).
Journal ArticleDOI
Unit Root Quantile Autoregression Inference
Roger Koenker,Zhijie Xiao +1 more
TL;DR: In this article, the limiting distribution of a quantile autoregression estimator and its t-statistic is derived, which is a linear combination of the Dickey-Fuller distribution and the standard normal, with the weight determined by the correlation coefficient of related time series.
Journal ArticleDOI
Regression Rank Scores and Regression Quantiles
TL;DR: In this article, regression quantiles and regression rank-scores are computed as solutions of a linear programming problem, and the solutions of the corresponding dual problem, which are called the regression rankscores, generalize the duality of order statistics and of ranks from the location to the linear model.
Journal ArticleDOI
Tests of linear hypotheses based on regression rank scores
TL;DR: In this paper, a general class of asymptotically distribution-free tests of a linear hypothesis in the linear regression model is proposed, which are based on regression rank scores.
Journal ArticleDOI
A double bootstrap method to analyze linear models with autoregressive error terms.
TL;DR: A new method for the analysis of linear models that have autoregressive errors is proposed, which is not only relevant in the behavioral sciences for analyzing small-sample time-series intervention models, but is also appropriate for a wide class of small- sample linear model problems.
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