solve error function $($expr$,$ width.cutoff $=60$L$,$ backtick $=$ mode$($expr$)\%$in$\%$

c$("$call$",$ "expression", $"(",$ "function"$),$ control $=$ c$("$keepNA$",$

"keepInteger", "niceNames", "showAttributes"$),$ nlines $=-1$L$)$

$.$Internal$($deparse$($expr$,$ width.cutoff, backtick, $.$deparseOpts$($control$),$

nlines$))$

code:

library$($methods$)$

randomVariate $<-$ function$($distFormula$,$ defs$)\{$

# Constructor method

obj $<-$ function$($n$)\{$

# Function to evaluate the formula and sample from distributions

eval$($distFormula$,$ defs, parent.frame$())$ # Evaluate the formula with provided definitions

$\}$

# Set class

class$($obj$)<-$ c$("$randomVariate$",$ class$($obj$))$

return$($obj$)$

$\}$

# Define print method for "randomVariate" objects

setMethod$("$show$",$ "randomVariate", function$($object$)\{$

cat$("$Formula:$",$ deparse$($object@distFormula$),"$

$")$

cat$("$Definitions:

$")$

for $($key in names$($object@defs$))\{$

cat$($key$,"---",$ deparse$($object@defs$[[$key$]]),"$

$")$

$\}$

$\})$

# Example usage

set.seed$(123)$ # for reproducibility

# Define a new random variable

newDist $<-$ randomVariate$($

distFormula $=$ ~x$^2,$

defs $=$ list$($x $=$ function$($n$)$ rnorm$($n$))$

$)$

# Print the object

print$($newDist$)$

# Generate a random sample

sample$1<-$ newDist$(10^5)$

# Plot a histogram of the sample

hist$($sample$1,$ breaks $=$ "Scott", probability $=$ TRUE, col $=$ rgb$(1,0,1,2),$ density $=20,$ angle $=45)$

lines$($density$($sample$1,$ adjust $=5),$ col $=$ rgb$(1,0,1,1))$