Fabian Scheipl

Fabian Scheipl

10 packages on CRAN

RLRsim

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Rapid, simulation-based exact (restricted) likelihood ratio tests for testing the presence of variance components/nonparametric terms for models fit with nlme::lme(),lme4::lmer(), lmeTest::lmer(), gamm4::gamm4(), mgcv::gamm() and SemiPar::spm().

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Bayesian variable selection, model choice, and regularized estimation for (spatial) generalized additive mixed regression models via stochastic search variable selection with spike-and-slab priors.

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Tools for 3D imaging, mostly for biology/microscopy. Read and write TIFF stacks. Functions for segmentation, filtering and analysing 3D point patterns.

dlnm

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Collection of functions for distributed lag linear and non-linear models.

gamm4

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Estimate generalized additive mixed models via a version of function gamm() from 'mgcv', using 'lme4' for estimation.

lme4

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Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

mboost

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Functional gradient descent algorithm (boosting) for optimizing general risk functions utilizing component-wise (penalised) least squares estimates or regression trees as base-learners for fitting generalized linear, additive and interaction models to potentially high-dimensional data.

mvtnorm

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Computes multivariate normal and t probabilities, quantiles, random deviates and densities.

pammtools

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The Piece-wise exponential (Additive Mixed) Model (PAMM; Bender and Scheipl (2018) <doi: 10.1177/1471082X17748083>) is a powerful model class for survival analysis, based on Generalized Additive (Mixed) Models (GA(M)Ms). It offers intuitive specification and robust estimation of complex survival models with stratified baseline hazards, random effects, time-varying effects, time-dependent covariates and cumulative effects (Bender et. al. (2018) <doi:10.1093/biostatistics/kxy003>. pammtools provides tidy workflow for survival analysis with PAMMs, including data transformation and other pre- and post-processing functions as well as visualization.

refund

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Methods for regression for functional data, including function-on-scalar, scalar-on-function, and function-on-function regression. Some of the functions are applicable to image data.