knitr::opts_chunk$set(echo=FALSE, warning=FALSE, message=FALSE) showplots <- FALSE
A sample was uploaded for the marginal distibution of the extension variable. Summary statistics and a histogram plot are as follows
options(digits = 4) summary(params$ry) library(ggplot2) df1 <- data.frame(Y = params$ry) ggplot(df1, aes(x = Y))+ geom_histogram(colour = "blue", fill = "white", bins = 30) + labs(title = "Histogram of sampled extension variable values") + theme_grey(base_size = 12)
fit <- params$fit2 bin.left <- NA bin.right <- NA chips <- NA roulette <- FALSE filename <- system.file("shinyAppFiles", "distributionsChild.Rmd", package="SHELF")
plotConditionalMedianFunction(yCP = params$yCP, xMed = params$xMed, yLimits = range(params$ry), link = params$link)
d2 <- switch(params$d[2],"normal" = "normal", "t" = "Student-t", "skewnormal" = "Skew normal", "gamma" = "gamma", "lognormal" = "log normal", "logt" = "log Student-t", "beta" = "beta", "hist" = "histogram", "best" = as.character(params$fit2$best.fitting[1, 1]), "mirrorgamma" = "mirror gamma", "mirrorlognormal" = "mirror log normal", "mirrorlogt" = "mirror log Student-t")
Marginal distribution of $X$, obtained using the uploaded sample for $Y$ and a r paste(d2)
distribution for $X|Y$:
library(ggplot2) ggplot(params$df1, aes(x = X, y = ..density..))+ geom_density(fill = "steelblue")+ theme_grey(base_size = 12)
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