Effects of ARMA Errors on the Significance Tests for Regression Coefficients
作者:
HrishikeshD. Vinod,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1976)
卷期:
Volume 71,
issue 356
页码: 929-933
ISSN:0162-1459
年代: 1976
DOI:10.1080/01621459.1976.10480971
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
It Is well known that nonindependent errors arising from autoregressive (AR) or moving average (MA) processes may reverse the conclusions oftorFtests for estimable functions of regression coefficients. We show that these conclusions can be reversed only if observedtorFvalues based on ordinary least squares (OLS) computations lie between certain lower and upper bounds. Our tabulations of these bounds are based on the Imhof [5] distribution of a ratio of quadratic forms in normal variables, and avoid some of the approximations used by Watson and Hannan [16].
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