# R/print.expectreg.R In expectreg: Expectile and Quantile Regression

#### Documented in print.expectreg

```print.expectreg <-
function(x,...)
{
cat("\nCall:\n", deparse(x\$formula), "\n", sep = "")
if(!inherits(x,"boost"))
{
cat("\nHead of Data:\n", sep = "")
if(x\$formula[[3]] != "1") {
dat = data.frame(cbind(x\$response,matrix(unlist(x\$covariates),nrow=length(x\$response)))[1:min(6,length(x\$response)),])
names(dat)[1] = attr(x\$response,"name")
if(length(x\$covariates)>1) {names(dat)[2:(length(x\$covariates)+1)] = names(x\$covariates)}
}
if(x\$formula[[3]] == "1") {
dat = data.frame(x\$response[1:min(6,length(x\$response))])
names(dat)[1] = attr(x\$response,"name")
}
print(dat)
cat("\n")
}
cat("\nFitted Expectiles:\n",  sep = "")
print(x\$asymmetries)
cat("\n")
if(!inherits(x,"boost"))
{
cat("\nSmoothing Parameters:\n",  sep = "")
print(x\$lambda)
cat("\n")
cat("\nIntercepts:\n", sep = "")
print(x\$inter)
cat("\n")
}
if(x\$formula[[3]] != "1") {
cat("\nRegression Coefficients:\n",  sep = "")
y = list()
for(i in 1:length(x\$coefficients))
{
if (x\$effects[[i]] == "random_interc")
y[[i]] = summary(x\$coefficients[[i]])
else y[[i]] = x\$coefficients[[i]][1:min(20, nrow(x\$coef[[i]])),]
names(y)[i] = names(x\$coefficients)[i]
}
print(y)
cat("\n")
}
invisible(x)

}
```

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expectreg documentation built on March 18, 2022, 5:57 p.m.