# powt: Power Transformation of Tree-Ring Data In dplR: Dendrochronology Program Library in R

 powt R Documentation

## Power Transformation of Tree-Ring Data

### Description

Perform power transformation for raw tree-ring width.

### Usage

powt(rwl, rescale = FALSE)
powt.series(series, rescale = FALSE)


### Arguments

 rwl a data.frame of raw tree-ring widths series, such as that produced by read.rwl or read.fh series a numeric vector, usually a tree-ring series. rescale logical flag. If TRUE then each transformed series is rescaled to have the orginal mean and standard deviation of the input data.

### Details

This procedure is a variance stabilization technique implemented after Cook & Peters (1997): for each series a linear model is fitted on the logs of level and spread, where level is defined as the local mean M_t = \left(R_t + R_{t-1}\right)/2 with ring widths R, and spread S is the local standard deviation defined as S_t = \left|R_t - R_{t-1}\right|. The regression coefficient b from \log S = k + b \log M is then used for the power transform \star{R}_t = R_t^{1-b}.

The rescale argument rescales the data to more closely follow the convention in ARSTAN.

### Value

Either 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 or in the case of a single series, a possibly named vector of the same. With rwl, the series IDs are the column names and the years are the row names.

### Author(s)

Christian Zang. Patched and improved by Mikko Korpela.

### References

Cook, E. R. and Peters, K. (1997) Calculating unbiased tree-ring indices for the study of climatic and environmental change. The Holocene, 7(3), 361–370.

rcs

### Examples

library(utils)
# many series at once
data(gp.rwl)
gp.pt <- powt(gp.rwl)
hist(summary(gp.rwl)$skew) hist(summary(gp.pt)$skew)

# single series
gp01A <- gp.rwl[, "01A"]
names(gp01A) <- rownames(gp.rwl)
gp01A.pt <- powt.series(gp01A,rescale=TRUE)
plot(gp01A.pt,gp01A)
abline(c(0,1))


dplR documentation built on June 22, 2024, 9:59 a.m.