Nothing
knitr::opts_chunk$set(echo=FALSE, warning=FALSE, message=FALSE, fig.pos = 'h', fig.align = 'center', fig.height = 3, fig.width = 4)
fit <- params$fit1 bin.left <- NA bin.right <- NA chips <- NA roulette <- FALSE filename <- system.file("shinyAppFiles", "distributionsChild.Rmd", package="SHELF")
fit <- params$fit2
d1 <- switch(params$d[1], "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$fit1$best.fitting[1, 1])) 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]))
Elicited concordance probability:
$$
P({X_1 < m_1,\, X_2 < m_2} \cup{ X_1>m_1, \, X_2 > m_2}) = r params$cp
$$
Joint sample, obtained using a r paste(d1)
distribution for $X_1$ and a r paste(d2)
distribution for $X_2$:
library(ggplot2) conc.probs <- matrix(0, 2, 2) conc.probs[1, 2] <- params$cp df1<-data.frame(copulaSample(params$fit1, params$fit2, cp=conc.probs, n=10000, d=params$d)) annotations <- data.frame( xpos = c(Inf,Inf,-Inf,-Inf), ypos = c(Inf, -Inf,-Inf,Inf), annotateText = as.character(c(params$cp / 2, 0.5 - params$cp /2, params$cp / 2, 0.5 - params$cp /2)), hjustvar = c(1.5, 1.5, -0.5, -0.5) , vjustvar = c(1.5, -0.5, -0.5, 1.5)) p1<-ggplot(data=df1,aes(x=X1, y=X2))+ geom_point(alpha=0.15, colour = "red") + geom_hline(yintercept = params$m2)+ geom_vline(xintercept = params$m1)+ labs(x=expression(X[1]), y = expression(X[2]))+ geom_text(data = annotations, aes(x = xpos, y = ypos, hjust = hjustvar, vjust = vjustvar, label = annotateText), size =10) + xlim(0.95*params$fit1$limits[1, 1], 1.05*params$fit1$limits[1, 2])+ ylim(0.95*params$fit2$limits[1, 1], 1.05*params$fit2$limits[1, 2]) suppressWarnings(suppressMessages(ggExtra::ggMarginal(p1, type = "histogram", fill = "red")))
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