## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) summary.DISTRIBUTION <- function(object,...) { knitr::kable(convdistr:::summary.DISTRIBUTION(object,...), digits = 2) } ## ----fig.width=7-------------------------------------------------------------- library(convdistr) library(ggplot2) a <- new_NORMAL(1,0.5) b <- new_POISSON(5) c <- new_BETA(10,20) res <- a + b * c metadata(res) summary(res) ggDISTRIBUTION(res) + ggtitle("a + b * c") ## ----echo=FALSE, results='hide'----------------------------------------------- sum_res <- convdistr:::summary.DISTRIBUTION(res) r_oval <- format(sum_res$oval, digits = 3) r_mean <- format(sum_res$mean_, digits = 3) r_median <- format(sum_res$median_, digits = 3) r_lci <- format(sum_res$lci_, digits = 2) r_uci <- format(sum_res$uci_, digits = 3) ## ----------------------------------------------------------------------------- myDistr <- new_NORMAL(0,1) metadata(myDistr) rfunc(myDistr, 10) summary(myDistr) ## ----fig.width=5, fig.cap = "Figure with R plot"------------------------------ plot(myDistr) ## ----fig.width=5, fig.cap = "Figure with ggplot2"----------------------------- ggDISTRIBUTION(myDistr) ## ----fig.width = 5------------------------------------------------------------ d1 <- new_NORMAL(1,1) d2 <- new_UNIFORM(2,8) d3 <- new_POISSON(5) dsum <- new_SUM(list(d1,d2,d3)) dsum d1 + d2 + d3 summary(dsum) ggDISTRIBUTION(dsum) ## ----fig.width = 7------------------------------------------------------------ d1 <- new_NORMAL(1,0.5) d2 <- new_NORMAL(5,0.5) d3 <- new_NORMAL(10,0.5) dmix <- new_MIXTURE(list(d1,d2,d3)) summary(dmix) ggDISTRIBUTION(dmix) ## ----fig.with = 7------------------------------------------------------------- d1 <- new_MULTINORMAL(c(0,1), matrix(c(1,0.3,0.3,1), ncol = 2), p_dimnames = c("A","B")) d2 <- new_MULTINORMAL(c(3,4), matrix(c(1,0.3,0.3,1), ncol = 2), p_dimnames = c("B","C")) summary(d1) summary(d2) summary(new_SUM_assoc(d1,d2)) summary(new_SUM_comb(d1,d2))