Testing in Mixed-Effects FANOVA Models
نویسندگان
چکیده
We consider the testing problem in the mixed-effects functional analysis of variance models. We develop asymptotically optimal (minimax) testing procedures for testing the significance of functional global trend and the functional fixed effects based on the empirical wavelet coefficients of the data. Wavelet decompositions allow one to characterize various types of assumed smoothness conditions on the response function under the nonparametric alternatives. The distribution of the functional random-effects component is defined in the wavelet domain and captures the sparseness of wavelet representation for a wide variety of functions. The simulation study presented in the paper demonstrates the finite sample properties of the proposed testing procedures. We also applied them to the real data from the physiological experiments.
منابع مشابه
Functional Analysis of Variance for Association Studies
While progress has been made in identifying common genetic variants associated with human diseases, for most of common complex diseases, the identified genetic variants only account for a small proportion of heritability. Challenges remain in finding additional unknown genetic variants predisposing to complex diseases. With the advance in next-generation sequencing technologies, sequencing stud...
متن کاملParameter Estimation in Spatial Generalized Linear Mixed Models with Skew Gaussian Random Effects using Laplace Approximation
Spatial generalized linear mixed models are used commonly for modelling non-Gaussian discrete spatial responses. We present an algorithm for parameter estimation of the models using Laplace approximation of likelihood function. In these models, the spatial correlation structure of data is carried out by random effects or latent variables. In most spatial analysis, it is assumed that rando...
متن کاملComparing two testing procedures in unbalanced two-way ANOVA models under heteroscedasticity: Approximate degree of freedom and parametric bootstrap approach
The classic F-test is usually used for testing the effects of factors in homoscedastic two-way ANOVA models. However, the assumption of equal cell variances is usually violated in practice. In recent years, several test procedures have been proposed for testing the effects of factors. In this paper, the two methods that are approximate degree of freedom (ADF) and parametric bootstr...
متن کاملTesting polynomial covariate effects in linear and generalized linear mixed models.
An important feature of linear mixed models and generalized linear mixed models is that the conditional mean of the response given the random effects, after transformed by a link function, is linearly related to the fixed covariate effects and random effects. Therefore, it is of practical importance to test the adequacy of this assumption, particularly the assumption of linear covariate effects...
متن کاملData-driven Kriging models based on FANOVA-decomposition
The situation of time consuming computer experiments is considered, where the output is deterministic and the data generating function is of high complexity. In such situations the underlying functions often are non additive but at the same time, not all interactions are active. Hence neither a model considering all interactions as well as an additive model is adequate. As a solution a modified...
متن کامل