powt | R Documentation |
Power transformation of tree-ring width.
powt(rwl, method = "universal", rescale = FALSE,
return.power=FALSE)
rwl |
a |
method |
a |
rescale |
|
return.power |
|
In dendrochronology, ring width series are sometimes power transformed to address heteroscedasticity.
The classic procedure used by method="cook"
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 a linear model
\log S = k + b \log M
is then used for the
power transform \star{R}_t = R_t^{1-b}
.
The procedure above is modified with method="universal"
where all samples
are used simultaneously in a linear mixed-effects model with time (year)
as a random effect: lmer(log S ~ log M + (1|year)
. This "universal" or
"signal free" approach accounts for the common year effect across all of the
series in rwl
and should address that not every year has the same
change in environmental conditions to the previous year.
The rescale
argument will return the series with a mean and standard
deviation that matches the input data. While this is a common convention,
users should note that this can produce negative values which can be confusing
if thought of as "ring widths."
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 class rwl
, the series IDs are the column names and the
years are the row names.
If return.power=TRUE
the returned
object is a list
containing the power transformed data and a
numeric
with the power estimate(s) used to transform the data.
Christian Zang implemented the Cook and Peters method. Stefan Klesse conceived and wrote the universal method. Patched and improved by Mikko Korpela and Andy Bunn.
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.
library(utils)
data(zof.rwl)
powtUniversal <- powt(zof.rwl, method = "universal")
powtCook <- powt(zof.rwl, method = "cook")
op <- par(no.readonly = TRUE)
par(mfcol = c(1, 3))
hist(summary(zof.rwl)$skew,
breaks = seq(-2.25,2.25,by=0.25),
main="Raw Data",xlab="Skew")
hist(summary(powtUniversal)$skew,
breaks = seq(-2.25,2.25,by=0.25),
main="Universal POWT",xlab="Skew")
hist(summary(powtCook)$skew,
breaks = seq(-2.25,2.25,by=0.25),
main="Cook POWT",xlab="Skew")
par(op) # restore graphical parameters
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