Exact likelihood ratio tests for penalised splines

By Ciprian M. Crainiceanu, David Ruppert, Gerda Claeskens, Matt P. Wand. 2005

140 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/afac41b9bd4fdaac73600923bac3864e50214cff

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In Control and Systems Engineering

In Statistics and Probability

Citations in the corpus

Determination of linear components in additive models (2011, methodology): “This fact implies that the penalised spline smoother under the framework in Equation (2) is equivalent to a standard LME (Brumback, Ruppert, and Wand 1999; Crainiceanu et al. 2005).”
Restricted Likelihood Ratio Testing for Zero Variance Components in Linear Mixed Models (2008, background): “While the power properties were not investigated in this article, Crainiceanu et al. (2005) have reported severe loss of power for the LRT.”
Non‐parametric small area estimation using penalized spline regression (2008, methodology): “Penalized spline regression, often referred to as P-splines, is a nonparametric method recently popularized by Eilers and Marx (1996). P-splines are an attractive smoothing method, because of their flexibility and the ability to incorporate them into a large range of modelling contexts.”
On p-values for smooth components of an extended generalized additive model (2013, background): “…of Tr suggests a usable choice for r. Existing work on the testing problem includes Cox et al. (1988), Liu & Wang (2004), Zhang & Lin (2003), Crainiceanu et al. (2005), Scheipl et al. (2008) and Nummi et al. (2011), but has usually focused on the hypothesis that Fj is a simple polynomial in…”
Bayesian semi parametric multi-state models (2008, background): “Although great efforts have been spent to extend the likelihood ratio theory in this direction (compare for example, Crainiceanu et al. (2005) or Greven et al. (forthcoming)), the methodology currently available is not readily applicable in our model class.”
A simple test for random effects in regression models (2013, methodology): “The latter is an approximation proposed by Greven et al. (2008) based on the exact test of Crainiceanu & Ruppert (2004) and Crainiceanu et al. (2005) and implemented in R (R Development Core Team, 2013) package RLRsim.”
Likelihood Ratio Tests for Dependent Data with Applications to Longitudinal and Functional Data Analysis (2014, methodology): “To avoid overfitting, we consider the approach proposed by Crainiceanu & Ruppert (2004) and Crainiceanu et al. (2005) and represent the mean function via an equivalent mixed-effects representation, .tij / D Xijˇ C Zij b, where Xij D .1; tij ; : : : ; tpij /, Zij D ° .tij 1/pC; : : : ; .tij K/ p C ±…”
The Hodrick-Prescott Filter A Special Case of Penalized Spline Smoothing (2010, methodology): “Dermoune et al. (2008). However, there is a vast existing body of work on the estimation of fixed and random components in LMMs, see for example Christensen (1996).”
Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models (2008, methodology): “The approximation of the null distribution of F λ 0 ,λ A by F(df(RSS 0 ) − df(RSS A ), df(RSS A )) is valid only for a fixed λ under the alternative (Crainiceanu et al., 2005).”