Package: bbmle 1.0.26

bbmle: Tools for General Maximum Likelihood Estimation

Methods and functions for fitting maximum likelihood models in R. This package modifies and extends the 'mle' classes in the 'stats4' package.

Authors:Ben Bolker [aut, cre], R Development Core Team [aut], Iago Giné-Vázquez [ctb]

bbmle_1.0.26.tar.gz
bbmle_1.0.26.zip(r-4.7)bbmle_1.0.26.zip(r-4.6)bbmle_1.0.26.zip(r-4.5)
bbmle_1.0.26.tgz(r-4.6-any)bbmle_1.0.26.tgz(r-4.5-any)
bbmle_1.0.26.tar.gz(r-4.7-any)bbmle_1.0.26.tar.gz(r-4.6-any)
bbmle_1.0.26.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
bbmle/json (API)

# Install 'bbmle' in R:
install.packages('bbmle', repos = c('https://bbolker.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bbolker/bbmle/issues

On CRAN:

Conda:

13.30 score 25 stars 151 packages 1.6k scripts 36k downloads 114 mentions 44 exports 6 dependencies

Last updated from:17e676755e. Checks:7 OK, 2 NOTE. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK217
source / vignettesOK196
linux-release-x86_64OK209
macos-release-arm64NOTE186
macos-oldrel-arm64NOTE164
windows-develOK179
windows-releaseOK170
windows-oldrelOK249
wasm-releaseOK108

Exports:AICAICcAICctabAICtabanovaBICtabcall.to.charcoefconfintdeviancednorm_nformulaICtablogLikmle2mle2.optionsnamedropparnamesparnames<-plotpop_pred_samppredictproffunprofileqAICqAICcrelist2residualssbetasbetabinomsbinomsimulatesliceslice1Dslice2DsliceOldslnormsnbinomsnormspoisstdErsummaryupdatevcov

Dependencies:bdsmatrixlatticeMASSMatrixmvtnormnumDeriv

Examples for enhanced mle code
Rendered frommle2.Rnwusingknitr::knitr

Last update: 2024-10-07
Started: 2016-11-17

quasi: notes on quasi-likelihood/qAIC analysis inR
Rendered fromquasi.Rnwusingknitr::knitr

Last update: 2022-05-06
Started: 2016-11-17

Readme and manuals

Help Manual

Help pageTopics
convert profile to data frameas.data.frame.profile.mle2 coerce,profile.mle2,data.frame-method coerce,profile.mle2-method
Log likelihoods and model selection for mle2 objectsAIC,mle2-method AIC-methods AICc AICc,ANY,mle2,logLik-method AICc,ANY-method AICc,logLik-method AICc,mle2-method AICc-methods anova,mle2-method BIC-methods logLik,mle2-method logLik-methods qAIC qAIC,ANY,mle2,logLik-method qAIC,ANY-method qAIC,logLik-method qAIC,mle2-method qAIC-methods qAICc qAICc,ANY,mle2,logLik-method qAICc,ANY-method qAICc,logLik-method qAICc,mle2-method qAICc-methods
Convert calls to charactercall.to.char
Normal distribution with profiled-out standard deviationdnorm_n
extract model namesget.mnames
Compute table of information criteria and auxiliary infoAICctab AICtab BICtab ICtab print.ICtab
Maximum Likelihood Estimationcalc_mle2_function mle mle2
Class "mle2". Result of Maximum Likelihood Estimation.coef,mle2-method coerce,mle,mle2-method deviance,mle2-method formula,mle2-method mle2-class show,mle2-method slice,mle2-method stdEr stdEr,mle2-method summary,mle2-method update,mle2-method vcov,mle2-method
Options for maximum likelihood estimationmle2.options
drop unneeded names from list elementsnamedrop
get and set parameter namesparnames parnames<-
generate population prediction sample from parameterspop_pred_samp
Predicted values from an mle2 fitgfun predict,mle2-method predict-methods residuals,mle2-method simulate,mle2-method
Likelihood profilesproffun profile,mle2-method profile-methods profile.mle2
Methods for likelihood profilesconfint,mle2-method confint,profile.mle2-method confint.mle2 plot,profile.mle2,missing-method plot,profile.mle2-method plot.profile.mle2 profile.mle2-class show,profile.mle2-method
reconstruct the structure of a listrelist2
Abstract definitions of distributionssbeta sbetabinom sbinom slnorm snbinom snorm spois
Calculate likelihood "slices"slice slice1D slice2D sliceOld slicetrans
likelihood-surface slicesslice.mle2-class
Wrap strings at white space and + symbolsstrwrapx
Class "summary.mle2", summary of "mle2" objectscoef,summary.mle2-method show,summary.mle2-method summary.mle2-class