## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.width=7, fig.height=7 ) ## ----setup-------------------------------------------------------------------- library(jagshelper) ## ----------------------------------------------------------------------------- library(jagshelper) skeleton("EXAMPLE") ## ----------------------------------------------------------------------------- nparam(asdf_jags_out) # how many parameters in total nbyname(asdf_jags_out) # how many parameters (or dimensions) per parameter name tracedens_jags(asdf_jags_out, parmfrow=c(3,3)) # trace plots for all parameters check_Rhat(asdf_jags_out) # proportion of Rhats below a threshold of 1.1 asdf_jags_out$Rhat # Rhat values ## ----------------------------------------------------------------------------- nparam(SS_out) # how many parameters in total nbyname(SS_out) # how many parameters (or dimensions) per parameter name traceworstRhat(SS_out, parmfrow=c(3,2)) # trace plots for least-converged nodes check_Rhat(SS_out) # proportion of Rhats below a threshold of 1.1 ## ----fig.width=6,fig.height=5------------------------------------------------- plotRhats(SS_out) # plotting Rhat values ## ----fig.width=7, fig.height=4------------------------------------------------ old_parmfrow <- par("mfrow") # storing previous graphics state par(mfrow=c(1, 2)) qq_postpred(ypp=SS_out, p="ypp", y=SS_data$y) ts_postpred(ypp=SS_out, p="ypp", y=SS_data$y) par(mfrow=old_parmfrow) # restoring previous graphics state ## ----fig.width=6-------------------------------------------------------------- pairstrace_jags(asdf_jags_out, p=c("a","sig_a"), points=TRUE, parmfrow=c(3,2)) ## ----fig.width=7, fig.height=6------------------------------------------------ plotcor_jags(SS_out, p=c("trend","rate","sig")) ## ----------------------------------------------------------------------------- out_df <- jags_df(asdf_jags_out) str(out_df) ## ----fig.width=5,fig.height=8------------------------------------------------- old_parmfrow <- par("mfrow") # storing old graphics state par(mfrow=c(3,1)) caterpillar(asdf_jags_out, "a") envelope(SS_out, "trend", x=SS_data$x) plotdens(asdf_jags_out, "a") par(mfrow=old_parmfrow) # resetting graphics state ## ----fig.width=5,fig.height=8------------------------------------------------- old_parmfrow <- par("mfrow") # storing old graphics state par(mfrow=c(2,1)) comparecat(x=list(asdf_jags_out, asdf_jags_out, asdf_jags_out), p=c("a","b","sig")) comparedens(x1=asdf_jags_out, x2=asdf_jags_out, p=c("a","b","sig")) par(mfrow=old_parmfrow) # resetting graphics state ## ----------------------------------------------------------------------------- par(mfrow=c(2,2)) ## usage with list of input data.frames overlayenvelope(df=list(SS_out$sims.list$cycle_s[,,1], SS_out$sims.list$cycle_s[,,2])) ## usage with a 3-d input array overlayenvelope(df=SS_out$sims.list$cycle_s) ## usage with a jagsUI output object and parameter name (2-d parameter) overlayenvelope(df=SS_out, p="cycle_s") ## usage with a single jagsUI output object and multiple parameters overlayenvelope(df=SS_out, p=c("trend","rate")) ## ----------------------------------------------------------------------------- ## Usage with single vectors (or data.frames or 2d matrices) xx <- SS_out$sims.list$trend[,41] yy <- SS_out$sims.list$cycle[,41] ## Showing possible geometries par(mfrow = c(2, 2)) plot(xx, yy, col=adjustcolor(1, alpha.f=.1), pch=16, main="Cross Geometry") crossplot(xx, yy, add=TRUE, col=1) plot(xx, yy, col=adjustcolor(1, alpha.f=.1), pch=16, main="X Geometry") crossplot(xx, yy, add=TRUE, col=1, drawcross=FALSE, drawx=TRUE) plot(xx, yy, col=adjustcolor(1, alpha.f=.1), pch=16, main="Blob Geometry") crossplot(xx, yy, add=TRUE, col=1, drawcross=FALSE, drawblob=TRUE) plot(xx, yy, col=adjustcolor(1, alpha.f=.1), pch=16, main="Blob Outlines") crossplot(xx, yy, add=TRUE, col=1, drawcross=FALSE, drawblob=TRUE, outline=TRUE) ## Usage with jagsUI object and parameter names, plus addl functionality par(mfrow = c(1, 1)) crossplot(SS_out, p=c("trend","cycle"), labels=SS_data$x, labelpos=1, link=TRUE, drawblob=TRUE, col="random") ## ----eval=FALSE--------------------------------------------------------------- # ... # sig ~ dunif(0, 10) # this is the parameter that is used elsewhere in the model # sig_prior ~ dunif(0, 10) # this is only used to give samples of the prior # ... ## ----------------------------------------------------------------------------- comparepriors(asdf_prior_jags_out, parmfrow=c(2,3))