Abstract
Abstract It Is well known that nonindependent errors arising from autoregressive (AR) or moving average (MA) processes may reverse the conclusions of t or F tests for estimable functions of regression coefficients. We show that these conclusions can be reversed only if observed t or F values 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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