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Wald tests of singular hypotheses. (English) Zbl 1388.62164

Summary: Motivated by the problem of testing tetrad constraints in factor analysis, we study the large-sample distribution of Wald statistics at parameter points at which the gradient of the tested constraint vanishes. When based on an asymptotically normal estimator, the Wald statistic converges to a rational function of a normal random vector. The rational function is determined by a homogeneous polynomial and a covariance matrix. For quadratic forms and bivariate monomials of arbitrary degree, we show unexpected relationships to chi-square distributions that explain conservative behavior of certain Wald tests. For general monomials, we offer a conjecture according to which the reciprocal of a certain quadratic form in the reciprocals of dependent normal random variables is chi-square distributed.

MSC:

62H15 Hypothesis testing in multivariate analysis
62F05 Asymptotic properties of parametric tests
62E20 Asymptotic distribution theory in statistics

Software:

TETRAD
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References:

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