Journal ArticleDOI
On the theory of testing serial correlation
Reads0
Chats0
TLDR
In this article, the Neyman-Pearson theory is applied to the problem of testing serial correlation in quadratic forms, and certain theorems concerning more general problems of Quadratic Form are developed and later applied to test serial correlation.Abstract:
Several different statistics have been proposed for testing the independence between successive observations from a normal population. In order to choose between the various tests a theory of testing this hypothesis in certain populations is needed. In this paper the problem is studied within the framework of the Neyman-Pearson theory. Certain theorems concerning more general problems of quadratic forms are developed and later applied to the question of testing serial correlation.read more
Citations
More filters
Journal ArticleDOI
Testing for serial correlation in least squares regression. II.
James Durbin,G. S. Watson +1 more
TL;DR: The problem of testing the errors for independence forms the subject of this paper and its successor and deals mainly with the theory on which the test is based, while the second paper describes the test procedures in detail and gives tables of bounds to the significance points of the test criterion adopted.
Journal ArticleDOI
Serial Correlation and the Fixed Effects Model
TL;DR: In this paper, the authors generalized the Durbin-Watson type statistics to test the OLS residuals from the fixed effects model for serial independence and developed a method for efficient estimation of the parameters.
Journal ArticleDOI
On the Theory of Testing for Unit Roots in Observed Time Series
TL;DR: In this article, a unit root null hypothesis for the errors affecting a classical regression model against the non-stationary (including explosive) alternative hypothesis is developed, and the test statistic is simplified in order that it could be viewed as a von Neumann type ratio and exact significance points are tabulated.
Book ChapterDOI
Chapter 46 Unit roots, structural breaks and trends
TL;DR: In this article, the authors present a review of inference about large autoregressive or moving average roots in univariate time series, and structural change in multivariate time-series regression.
MonographDOI
Generalized Least Squares
Takeaki Kariya,Hiroshi Kurata +1 more
TL;DR: In this paper, a nonlinear version of the Gauss-Markov Theorem is used for estimating the risk matrix of a least square estimator in a two-equation Heteroscedastic model.
References
More filters
Book ChapterDOI
On the Problem of the Most Efficient Tests of Statistical Hypotheses
Jerzy Neyman,Egon S. Pearson +1 more
TL;DR: The problem of testing statistical hypotheses is an old one as discussed by the authors and its origins are usually connected with the name of Thomas Bayes, who gave the well-known theorem on the probabilities a posteriori of the possible causes of a given event.
Journal ArticleDOI
On the problems of the most efficient tests of statistical hypotheses.
J. Neyman,E. S. Pearson +1 more
TL;DR: The problem of testing statistical hypotheses is an old one as discussed by the authors, and its origin is usually connected with the name of Thomas Bayes, who gave the well-known theorem on the probabilities a posteriori of the possible causes of a given event.
Journal ArticleDOI