The power of the likelihood ratio test of location in nonlinear regression models

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The Likelihood Ratio Test statistic, T, is considered for the hypothesis H: θ = θ0against A: θ ≠ θ0in the nonlinear regression model y = f(x, θ) + e with normal errors and unknown variance. The distribution function of a random variable X such that n · (T — X) converges in probability to zero is derived. Using X to approximate T, the power of the Likelihood Ratio Test is tabulated for selected sample sizes and departures from the null hypothesis. The adequacy of the approximation of T by X is investigated in a Monte-Carlo study.

Original languageEnglish (US)
Pages (from-to)198-203
Number of pages6
JournalJournal of the American Statistical Association
Issue number349
Publication statusPublished - Mar 1975


All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

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