## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", message = FALSE ) ## ----setup-------------------------------------------------------------------- library(ameras) ## ----------------------------------------------------------------------------- data(data, package="ameras") head(data) ## ----modelfit.linreg, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(12345) fit.ameras.linreg <- ameras(Y.gaussian~dose(V1:V10)+X1+X2, data=data, family="gaussian", niter.BMA=5000, nburnin.BMA=1000, methods=c("RC", "ERC", "MCML", "FMA", "BMA")) ## ----eval = identical(Sys.getenv("NOT_CRAN"), "true")------------------------- str(fit.ameras.linreg) ## ----eval = identical(Sys.getenv("NOT_CRAN"), "true")------------------------- fit.ameras.linreg$RC ## ----eval = identical(Sys.getenv("NOT_CRAN"), "true")------------------------- summary(fit.ameras.linreg) ## ----eval = identical(Sys.getenv("NOT_CRAN"), "true")------------------------- coef(fit.ameras.linreg) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- traceplot(fit.ameras.linreg) ## ----modelfit.logreg, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(33521) fit.ameras.logreg <- ameras(Y.binomial~dose(V1:V10, deg=2, model="EXP")+X1+X2, data=data, family="binomial", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.logreg) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.logreg) ## ----modelfit.logreg.lin, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(3521216) fit.ameras.logreg.lin <- ameras(Y.binomial~dose(V1:V10, deg=1, model="EXP")+X1+X2, data=data, family="binomial", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.logreg.lin) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.logreg.lin) ## ----modelfit.poisson, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(332101) fit.ameras.poisson <- ameras(Y.poisson~dose(V1:V10, deg=2, model="EXP")+X1+X2, data=data, family="poisson", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.poisson) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.poisson) ## ----modelfit.poisson.lin, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(24252) fit.ameras.poisson.lin <- ameras(Y.poisson~dose(V1:V10, deg=1, model="EXP")+X1+X2, data=data, family="poisson", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.poisson.lin) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.poisson.lin) ## ----modelfit.prophaz, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(332120000) fit.ameras.prophaz <- ameras(Surv(time, status)~ dose(V1:V10, deg=2, model="EXP")+X1+X2, data=data, family="prophaz", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.prophaz) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.prophaz) ## ----eval = identical(Sys.getenv("NOT_CRAN"), "true")------------------------- fit.ameras.prophaz$BMA$prophaz.timepoints ## ----modelfit.prophaz.lin, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(24978252) fit.ameras.prophaz.lin <- ameras(Surv(time, status)~ dose(V1:V10, deg=1, model="EXP")+X1+X2, data=data, family="prophaz", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.prophaz.lin) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.prophaz.lin) ## ----modelfit.multinomial, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(33) fit.ameras.multinomial <- ameras(Y.multinomial~ dose(V1:V10, deg=2, model="EXP")+X1+X2, data=data, family="multinomial", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.multinomial) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.multinomial) ## ----modelfit.multinomial.lin, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(44) fit.ameras.multinomial.lin <- ameras(Y.multinomial~ dose(V1:V10, deg=1, model="EXP")+X1+X2, data=data, family="multinomial", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.multinomial.lin) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.multinomial.lin) ## ----modelfit.clogit, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(3301) fit.ameras.clogit <- ameras(Y.clogit~dose(V1:V10, deg=2, model="EXP")+X1+X2+ strata(setnr), data=data, family="clogit", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.clogit) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.clogit) ## ----modelfit.clogit.lin, cache=TRUE, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- set.seed(4401) fit.ameras.clogit.lin <- ameras(Y.clogit~dose(V1:V10, deg=2, model="EXP")+X1+X2+ strata(setnr), data=data, family="clogit", methods=c("RC", "ERC", "MCML", "FMA", "BMA"), niter.BMA = 5000, nburnin.BMA = 1000) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- summary(fit.ameras.clogit.lin) ## ----fig.fullwidth=TRUE, fig.show="hold", out.width='100%', fig.width=6, fig.height=8, eval = identical(Sys.getenv("NOT_CRAN"), "true")---- coef(fit.ameras.clogit.lin)