Package index • actuaRE

All functions

actuaRE-package actuaRE: Handling Single-Level and Hierarchically Structured Risk Factors using Credibility and Random Effects Models

adjustIntercept(): Adjust the intercept to regain the balance property

BalanceProperty(): Balance property

predict(<buhlmannStraub>) print(<buhlmannStraub>) summary(<buhlmannStraub>) fitted(<buhlmannStraub>): Class "buhlmannStraub" of fitted Buhlmann-Straub credibility models

buhlmannStraub(): Buhlmann-Straub credibility model

predict(<buhlmannStraubGLM>) print(<buhlmannStraubGLM>) summary(<buhlmannStraubGLM>) fitted(<buhlmannStraubGLM>): Class "buhlmannStraubGLM" of fitted Buhlmann-Straub GLM credibility models

buhlmannStraubGLM(): Combining the Buhlmann-Straub credibility model with a GLM (Ohlsson, 2008)

predict(<buhlmannStraubTweedie>) print(<buhlmannStraubTweedie>) summary(<buhlmannStraubTweedie>) fitted(<buhlmannStraubTweedie>): Class "buhlmannStraubTweedie" of fitted Buhlmann-Straub GLM credibility models

buhlmannStraubTweedie(): Combining the Buhlmann-Straub credibility model with a Tweedie GLM (Ohlsson, 2008)

dataCar: data Car

.addREs(): Add random effects to the data frame

.oldtweedieGLMM(): Fitting a Tweedie GLMM, using the initial estimates of hierCredTweedie

findbars(): Determine random-effects expressions from a formula

fixef(<hierCredGLM>) fixef(<hierCredTweedie>) fixef(<buhlmannStraubGLM>) fixef(<buhlmannStraubTweedie>): Extract the fixed-effects estimates from a fitted random effects model

fixed.effects fixef: Extract fixed-effects estimates

hachemeisterLong: Hachemeister Data Set

print(<hierCredGLM>) summary(<hierCredGLM>) fitted(<hierCredGLM>): Class "hierCredGLM" of fitted random effects models estimated with Ohlsson's GLMC algorithm

hierCredGLM(): Combining the hierarchical credibility model with a GLM (Ohlsson, 2008)

print(<hierCredibility>) summary(<hierCredibility>) fitted(<hierCredibility>): Class "hierCredibility" of fitted hierarchical credibility models

hierCredibility(): Hierarchical credibility model of Jewell

print(<hierCredTweedie>) summary(<hierCredTweedie>) fitted(<hierCredTweedie>): Class "hierCredTweedie" of fitted random effects models estimated with Ohlsson's GLMC algorithm

hierCredTweedie(): Combining the hierarchical credibility model with a GLM (Ohlsson, 2008)

is.formula(): Formula

isNested(): Is f1 nested within f2?

glFormula(): Modular Functions for Mixed Model Fits

nobars(): Omit terms separated by vertical bars in a formula

NrUnique(): Number of unique elements in a vector

plotRE(): Visualizing the random effect estimates using ggplot2

predict(<hierCredGLM>): Model predictions

predict(<hierCredibility>): Model predictions

predict(<hierCredTweedie>): Model predictions

print(<BalanceProperty>): Print method for an object of class BalanceProperty

ranef(<hierCredibility>) ranef(<hierCredGLM>) ranef(<hierCredTweedie>) ranef(<buhlmannStraubGLM>) ranef(<buhlmannStraub>) ranef(<buhlmannStraubTweedie>): Extract the random effect estimates from a fitted random effects model

ranef: Extract the modes of the random effects

tweedieGLMM(): Fitting a Tweedie GLMM, using initial estimates from credibility models

tweedietraindata tweedietestdata: Simulated data sets to illustrate the package functionality

weights(<cpglm>) weights(<hierCredGLM>) weights(<hierCredTweedie>) weights(<buhlmannStraubGLM>) weights(<buhlmannStraubTweedie>): Extract the model weights