Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

One character typo: d/q/p/q -> d/q/p/r #445

Merged
merged 1 commit into from
Mar 9, 2016
Merged

One character typo: d/q/p/q -> d/q/p/r #445

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
10 changes: 4 additions & 6 deletions vignettes/Rcpp-sugar.Rnw
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -104,7 +104,7 @@ The goal of the function \texttt{foo} code is simple. Given two

<<eval=FALSE>>=
foo <- function(x, y){
ifelse( x < y, x*x, -(y*y) )
ifelse( x < y, x*x, -(y*y) )
}
@

Expand Down Expand Up @@ -218,7 +218,6 @@ NumericVector res = -x ;
// use it as part of a numerical expression
NumericVector res = -x * ( x + 2.0 ) ;


// two integer vectors of the same size
NumericVector y ;
NumericVector z ;
Expand All @@ -243,7 +242,6 @@ given a logical sugar expression.
<<lang=cpp>>=
IntegerVector x = seq_len( 1000 ) ;
all( x*x < 3 ) ;

any( x*x < 3 ) ;
@

Expand Down Expand Up @@ -448,7 +446,7 @@ pow(x, z) # x to the power of z

% log() and log10() maybe? Or ln() ?

\subsection{The d/q/p/q statistical functions}
\subsection{The d/q/p/r statistical functions}

The framework provided by \sugar also permits easy and efficient access the
density, distribution function, quantile and random number generation
Expand All @@ -460,8 +458,8 @@ would in \proglang{R}:

<<lang=cpp>>=
x1 = dnorm(y1, 0, 1); // density of y1 at m=0, sd=1
x2 = pnorm(y2, 0, 1); // distribution function of y2
x3 = qnorm(y3, 0, 1); // quantiles of y3
x2 = qnorm(y2, 0, 1); // quantiles of y2
x3 = pnorm(y3, 0, 1); // distribution function of y3
x4 = rnorm(n, 0, 1); // 'n' RNG draws of N(0, 1)
@

Expand Down