powt {dplR}  R Documentation 
Perform power transformation for raw treering width.
powt(rwl, rescale = FALSE)
powt.series(series, rescale = FALSE)
rwl 
a 
series 
a 
rescale 

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_{t1}\right)/2
with
ring widths R, and spread S is the local standard deviation defined as
S_t = \leftR_t  R_{t1}\right
. The
regression coefficient b from \log S = k + b \log M
is then used for the power transform \star{R}_t =
R_t^{1b}
.
The rescale
argument rescales the data to more closely follow the
convention in ARSTAN.
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.
Christian Zang. Patched and improved by Mikko Korpela.
Cook, E. R. and Peters, K. (1997) Calculating unbiased treering indices for the study of climatic and environmental change. The Holocene, 7(3), 361–370.
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))