\HeaderA{arrayWeightsQuick}{Array Quality Weights}{arrayWeightsQuick}
\keyword{regression}{arrayWeightsQuick}
\begin{Description}\relax
Estimates relative quality weights for each array in a multi-array experiment with replication.
\end{Description}
\begin{Usage}
\begin{verbatim}
arrayWeightsQuick(y, fit)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{y}] the data object used to estimate \code{fit}.
Can be of any class which can be coerced to matrix, including \code{matrix}, \code{MAList}, \code{marrayNorm} or \code{exprSet}.
\item[\code{fit}] \code{MArrayLM} fitted model object
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
Estimates the relative reliability of each array by measuring how well the expression values for that array follow the linear model.

This is a quick and dirty version of \code{\LinkA{arrayWeights}{arrayWeights}}.
\end{Details}
\begin{Value}
Numeric vector of weights of length \code{ncol(fit)}.
\end{Value}
\begin{Author}\relax
Gordon Smyth
\end{Author}
\begin{References}\relax
Ritchie, M. E., Diyagama, D., Neilson, van Laar, R., J., Dobrovic, A., Holloway, A., and Smyth, G. K. (2006). Empirical array quality weights for microarray data. BMC Bioinformatics. (Accepted 11 April 2006)
\end{References}
\begin{SeeAlso}\relax
See \LinkA{arrayWeights}{arrayWeights}.
An overview of LIMMA functions for reading data is given in \LinkA{03.ReadingData}{03.ReadingData}.
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
## Not run: 
fit <- lmFit(y, design)
arrayWeightsQuick(y, fit)
## End(Not run)
\end{ExampleCode}
\end{Examples}