Nothing
## ----setopts,echo=FALSE,message=FALSE, eval = TRUE----------------------------
library("knitr")
opts_chunk$set(fig.width=5,fig.height=5,
out.width="0.8\\textwidth",
echo = TRUE, error = FALSE,
eval = identical(Sys.getenv("NOT_CRAN"), "true"))
Rver <- paste(R.version$major,R.version$minor,sep=".")
used.pkgs <- c("glmmTMB","bbmle") ## packages to report below
## ----pkgversions, echo=FALSE, eval=TRUE---------------------------------------
pkgver <- vapply(sort(used.pkgs),function(x) as.character(packageVersion(x)),"")
print(pkgver,quote=FALSE)
## ----citation,eval=FALSE,echo=FALSE-------------------------------------------
# print(citation("glmmTMB"),style="latex")
## ----pkgs,message=FALSE, eval=TRUE--------------------------------------------
library("glmmTMB")
library("bbmle") ## for AICtab
library("ggplot2")
## cosmetic
theme_set(theme_bw()+
theme(panel.spacing=grid::unit(0,"lines")))
## ----owltransform,warning=FALSE-----------------------------------------------
# Owls <- transform(Owls,
# Nest=reorder(Nest,NegPerChick),
# NCalls=SiblingNegotiation,
# FT=FoodTreatment)
## ----owlplot1,echo=FALSE,message=FALSE,warning=FALSE,eval=FALSE---------------
# G0 <- ggplot(Owls,aes(x=reorder(Nest,NegPerChick),
# y=NegPerChick))+
# labs(x="Nest",y="Negotiations per chick")+coord_flip()+
# facet_grid(FoodTreatment~SexParent)
# G0+stat_sum(aes(size=..n..),alpha=0.5)+
# scale_size_continuous(name="# obs",
# breaks=seq(1,9,by=2))+
# theme(axis.title.x=element_text(hjust=0.5,size=12),
# axis.text.y=element_text(size=7))
## ----glmmTMBfit---------------------------------------------------------------
# fit_zipoisson <- glmmTMB(NCalls~(FT+ArrivalTime)*SexParent+
# offset(log(BroodSize))+(1|Nest),
# data=Owls,
# ziformula=~1,
# family=poisson)
## ----zipoisssum---------------------------------------------------------------
# summary(fit_zipoisson)
## ----glmmTMBnbinomfit---------------------------------------------------------
# fit_zinbinom <- update(fit_zipoisson,family=nbinom2)
## ----glmmTMBnbinom1fit--------------------------------------------------------
# fit_zinbinom1 <- update(fit_zipoisson,family=nbinom1)
## ----glmmTMBnbinom1vfit-------------------------------------------------------
# fit_zinbinom1_bs <- update(fit_zinbinom1,
# . ~ (FT+ArrivalTime)*SexParent+
# BroodSize+(1|Nest))
## ----aictab-------------------------------------------------------------------
# AICtab(fit_zipoisson,fit_zinbinom,fit_zinbinom1,fit_zinbinom1_bs)
## ----glmmTMBnbinomhfit--------------------------------------------------------
# fit_hnbinom1 <- update(fit_zinbinom1_bs,
# ziformula=~.,
# data=Owls,
# family=truncated_nbinom1)
## ----hurdle_AIC---------------------------------------------------------------
# AICtab(fit_zipoisson,fit_zinbinom,
# fit_zinbinom1,fit_zinbinom1_bs,
# fit_hnbinom1)
## ----contraception_sum,echo=FALSE, eval=TRUE----------------------------------
data("Contraception",package="mlmRev")
nc <- nrow(Contraception)
nl <- length(levels(Contraception$district))
load("contraceptionTimings.rda")
meandiff <- mean(with(tmatContraception,
time[pkg=="glmer"]/time[pkg=="glmmTMB"]))
## ----contraception,echo=FALSE,warning=FALSE,fig.cap="Timing for fitting the replicated Contraception data set."----
# ## NaN from geom_smooth because glmmADMB only has two points/
# ## can't compute confidence intervals
# ## suppressWarnings() doesn't actually work within ggplot ...
# ## instead set/reset options("warn")
# op <- options(warn = -1)
# ggplot(tmatContraception,
# aes(n, time, colour=pkg)) + geom_point() +
# scale_y_log10(breaks=c(1,2,5,10,20,50,100)) +
# scale_x_log10(breaks=c(1,2,4,10,20,40)) +
# labs(x="Replication (x 1934 obs.)",y="Elapsed time (s)") +
# geom_smooth(method="lm", formula = y ~ x) +
# scale_colour_brewer(palette="Set1")
# options(op)
## ----insteval,echo=FALSE,warning=FALSE,fig.cap="Timing for fitting subsets of the InstEval data set.", eval = TRUE----
load("InstEvalTimings.rda")
n_InstEval <- 73421L ## seems silly to require lme4 just to get this number
meandiff_inst2 <- with(tmatInstEval,
time[pkg=="lmer"]/time[pkg=="glmmTMB"])
ggplot(tmatInstEval,aes(n,time,colour=pkg))+geom_point()+
scale_y_log10(breaks=c(1,2,5,10,20,50,100,200))+
scale_x_log10(breaks=c(0.1,0.2,0.5,1.0))+
labs(x=sprintf("Replication (x %d obs.)",n_InstEval),
y="Elapsed time (s)")+
geom_smooth(method="lm", formula = y ~ x)+
scale_colour_brewer(palette="Set1")
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