\HeaderA{zscore}{Z-score Equivalents}{zscore}
\aliasA{tZscore}{zscore}{tZscore}
\aliasA{zscoreGamma}{zscore}{zscoreGamma}
\aliasA{zscoreT}{zscore}{zscoreT}
\keyword{distribution}{zscore}
\begin{Description}\relax
Compute z-score equivalents of for gamma or t-distribution random deviates.
\end{Description}
\begin{Usage}
\begin{verbatim}
zscoreGamma(q, shape, rate = 1, scale = 1/rate) 
zscoreT(x, df)
tZscore(x, df)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{q, x}] numeric matrix for vector giving deviates of a random variaable
\item[\code{shape}] gamma shape parameter (>0)
\item[\code{rate}] gamma rate parameter (>0)
\item[\code{scale}] gamma scale parameter (>0)
\item[\code{df}] degrees of freedom (>0 for \code{zscore} or >=1 for \code{tZscore})
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
These functions compute the standard normal deviates which have the same quantiles as the given values in the specified distribution.
For example, if \code{z <- zscoreT(x,df=df)} then \code{pnorm(z)} equals \code{pt(x,df=df)}.
\code{tZscore} is the inverse of \code{zscoreT}.

Care is taken to do the computations accurately in both tails of the distributions.
\end{Details}
\begin{Value}
Numeric vector giving equivalent deviates from a standard normal distribution (\code{zscoreGamma} and \code{zscoreT}) or deviates from a t-distribution (\code{tZscore}).
\end{Value}
\begin{Author}\relax
Gordon Smyth
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{qnorm}{qnorm}}, \code{\LinkA{pgamma}{pgamma}}, \code{\LinkA{pt}{pt}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
zscoreGamma(1, shape=1, scale=1)
zscoreT(2, df=3)
tZscore(2, df=3)
\end{ExampleCode}
\end{Examples}