Hostname: page-component-848d4c4894-nr4z6 Total loading time: 0 Render date: 2024-04-30T22:34:16.407Z Has data issue: false hasContentIssue false

Approximate distributions of Student's t-statistics for autoregressive coefficients calculated from regression residuals

Published online by Cambridge University Press:  14 July 2016

Abstract

We consider a multiple regression model in which the regressors are Fourier cosine vectors. These regressors are intended as approximations to ‘slowly changing' regressors of the kind often found in time series regression applications. The errors in the model are assumed to be generated by a special type of autoregressive model defined so that the regressors are eigenvectors of the quadratic forms occurring in the exponent of the probability density of the errors. This autoregression is intended as an approximation to the usual stationary autoregression. Both approximations are adopted for the sake of mathematical convenience.

Student's t-statistics are constructed for the autoregressive coefficients in a manner analogous to ordinary regression. It is shown that these statistics are distributed as Student's t to the first order of approximation, that is with errors in the density of order T−1/2, where T is the sample size, while the squares of the statistics are distributed as the square of Student's t to the second order of approximation, that is with errors in the density of order Τ–1.

Type
Part 3—Hypothesis Testing and Distribution Theory for Time Series
Copyright
Copyright © 1986 Applied Probability Trust 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Daniels, H. E. (1956) The approximate distribution of serial correlation coefficients. Biometrika 43, 169185.Google Scholar
Durbin, J. (1980) The approximate distribution of partial serial correlation coefficients calculated from residuals from regression on Fourier series. Biometrika 67, 335349.Google Scholar
Durbin, J. (1983) The price of ignorance of the autocorrelation structure of the errors of a regression model. Studies in Econometrics, Time Series and Multivariate Statistics , ed. Karlin, S., Amemiya, T. and Goodman, L. A. Academic Press, New York.Google Scholar
Durbin, J. (1984) Time series analysis. J. R. Statist. Soc. A 147, 161173.Google Scholar
Hannan, E. J. (1960) Time Series Analysis. Methuen, London.Google Scholar
Leipnik, R. B. (1947) Distribution of the serial correlation coefficient in a circularly correlated universe. Ann. Math. Statist. 18, 8087.Google Scholar
Mann, H. B. and Wald, A. (1943) On the statistical treatment of linear stochastic difference equations. Econometrica 11. 173220.Google Scholar
Quenouille, M. H. (1949) Approximate tests of correlation in time series 3. Proc. Camb. Phil. Soc. 45. 483484.Google Scholar