A Test for a Shifting Slope Coefficient in a Linear Model
作者:
JohnU. Farley,
MelvinJ. Hinich,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1970)
卷期:
Volume 65,
issue 331
页码: 1320-1329
ISSN:0162-1459
年代: 1970
DOI:10.1080/01621459.1970.10481167
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
A locally most powerful test is developed for the hypothesis that a slope coefficient in a linear time series model is stable, against the alternative that the slope shifts exactly once somewhere in the series. Analysis of the procedure using artificial data indicates good power characteristics even when the ratio of the shift size to the error variance is moderate—especially if the shift does not occur very near either end of the series. Power also depends on the pattern of the independent variables and on whether the error variance is known or must be estimated using the residuals about the regression line.
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