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FDboost - Boosting Functional Regression Models
Regression models for functional data, i.e., scalar-on-function, function-on-scalar and function-on-function regression models, are fitted by a component-wise gradient boosting algorithm. For a manual on how to use 'FDboost', see Brockhaus, Ruegamer, Greven (2017) <doi:10.18637/jss.v094.i10>.
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boostingboosting-algorithmsfunction-on-function-regressionfunction-on-scalar-regressionmachine-learningscalar-on-function-regressionvariable-selection
9.03 score 21 stars 130 scripts 5.4k downloadscAIC4 - Conditional Akaike Information Criterion for 'lme4' and 'nlme'
Provides functions for the estimation of the conditional Akaike information in generalized mixed-effect models fitted with (g)lmer() from 'lme4', lme() from 'nlme' and gamm() from 'mgcv'. For a manual on how to use 'cAIC4', see Saefken et al. (2021) <doi:10.18637/jss.v099.i08>.
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4.19 score 2 stars 1 dependents 128 scripts 5.1k downloads