Restricted likelihood ratio lack‐of‐fit tests using mixed spline models

By Gerda Claeskens. 2004

50 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/fa290ade19f3e82e99657fc2c55c7df528364767

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Citations in the corpus

Small area estimates of labour force participation under a multinomial logit mixed model (2007, methodology): “Under the null hypothesis ϕ=0, the likelihood ratio test statistic is distributed as a mixture of two χ2-distributions with 0 and 1 degrees of freedom; more precisely, 0:5χ20 +0:5χ21 (see Self and Liang (1987) or Claeskens (2004)).”
Semiparametric inference in generalized mixed effects models (2008, methodology): “Opsomer et al. (2008) proposed a restricted likelihood ratio test for small area effects and non-linearities with splines, following the ideas of Claeskens (2004).”
Non‐parametric small area estimation using penalized spline regression (2008, result): “To prove the first part of the theorem, we follow the same line of arguments as to prove Theorem 2 of Claeskens (2004), with the difference that only one variance component is set to zero.”
Nonparametric small area estimation using penalized spline regression (2005, unknown): “To prove the first part of the theorem, we follow the same line of arguments as to prove Theorem 2 of Claeskens (2004), with the difference that only one variance component is set to zero.”
Determination of linear components in additive models (2011, methodology): “Asymptotic properties and smoothing parameter selection of a penalised spline estimator can be found in Wand (1999), Hall and Opsomer (2005), Li and Ruppert (2008), and Claeskens, Krivobokova, and Opsomer (2008). Penalised spline smoothing for the partially linear model in a more general setting has”