Nothing
## ---- echo=FALSE,message=FALSE, warning=FALSE---------------------------------
#devtools::load_all()
## -----------------------------------------------------------------------------
library(cdfquantreg)
data(cdfqrExampleData)
ipcc_mid <- subset(IPCC, mid == 1 & high == 0)
# Overview the data
knitr::kable(head(ipcc_mid), row.names=F)
# Distribution of the data
MASS::truehist(ipcc_mid$probm)
# Choice of CDF distribution: finite tailed
cdfqrFamily(shape='FT')
## ----fit----------------------------------------------------------------------
# We use T2-T2 distribution
fd <- "t2"
sd <- "t2"
# Fit the null model
fit_null <- cdfquantreg(probm ~ 1 | 1, fd, sd, data = ipcc_mid)
# Fit the target model
fit <- cdfquantreg(probm ~ valence | valence, fd, sd, data = ipcc_mid)
# Obtain the statistics for the null model
summary(fit)
## ----plotfit, fig.width= 7----------------------------------------------------
# Compare the empirical distribution and the fitted values distribution
plot(fit)
# Plot the fitted values
plot(fitted(fit, "full"))
# Check Residuals
plot(residuals(fit, "raw"))
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