sklesse
commented
1 week ago \name{universalPOWT{dplR}} \alias{universalPOWT{dplR}}}
\title{ Universal power transformation } \description{ This function estimates the power of the spread-vs-level relationship of raw tree-ring data on the population level. That means every individual time series gets transformed with the same power estimate. The function includes the common inter-annual variability in the power estimation, it is signal-free, so-to-say. } \usage{ universalPOWT(rwl,return.power=FALSE) } %- maybe also 'usage' for other objects documented here. \arguments{ \item{rwl}{a data.frame of raw tree-ring widths series, such as that produced by read.rwl or read.fh} \item{return.power}{logical flag. If TRUE then the power estimate is returned} } \details{ This procedure is an update of the variance stabilization technique of Cook & Peters (1997). Instead of fitting a linear model on the logs of level and spread of each individual series, this function fits the model on the whole population. In addition, the model accounts for the common year-to-year variability in the spread-vs-level relationship.
} \value{
If return.power is FALSE (the default), an object of class c("rwl", "data.frame") containing the power transformed ring-width series with the series in columns and the years as rows.
If return.power is TRUE, the return value is a list with two parts: \item{transformed.data}{the power transformed data} \item{power}{the power estimate used to transform the data} %% ... } } \author{ Stefan Klesse }
\examples{ data(zof.rwl) zof.pt <- universalPOWT(zof.rwl)
compare to
zof.pt.old <- powt(zof.rwl)
population-based power estimation to transform the tree-ring data