chron.ars  R Documentation 
This function builds three varieties of the meanvalue chronology, including
the ARSTAN chronology, typically from a
data.frame
of detrended ring widths as produced by
detrend
.
chron.ars(x, biweight=TRUE, maxLag=10, firstAICmin=TRUE,
verbose=TRUE, prewhitenMethod=c("ar.yw","arima.CSSML"))
x 
a 
biweight 

maxLag 
an 
firstAICmin 

verbose 

prewhitenMethod 
a 
This produces three meanvalue chronologies: standard, residual, and ARSTAN. Users unfamiliar with the concept behind the ARSTAN method should look to Cook (1985) for background and inspiration.
The standard chronology is the (biweight) mean value across rows and identical to chron
.
The residual chronology is the prewhitened chronology as described by Cook (1985) and uses uses multivariate autoregressive modeling to determine the order of the AR process. It's important to note that residual chronology produced here is different than the simple residual chronology produced by chron
which returns the residuals of an AR process using a naive call to ar
. But in practice the results will be similar. For more on the residual chronology in this function, see pp. 153154 in Cook's 1985 dissertation.
The ARSTAN chronology builds on the residual chronology but returns a rewhitened chronology where the pooled AR coefficients from the multivariate autoregressive modeling are reintroduced. See references for details.
The order of the AR model is selected from the pooled AR coefficients by AIC using either the first (local) AIC minimum otherwise or the overall minimum considering the maximum lag (argument maxLag
).
Once the AR order is determined an AR(p) model is fit using either ar
via the YuleWalker method or by arima
via conditionalsumofsquares to find starting values, then maximum likelihood. It is possible that the model will not converge in which case a warning is produced. The AR fitting is determined via prewhitenMethod
and defaults to using ar
.
A data.frame
with the standard, residual, and ARSTAN chronologies. The sample depth is also included.
Andy Bunn with contributions from Kevin Achukaitis and Ed Cook. Much of the function is a port of Cook's FORTRAN code.
Cook, E. R. and Kairiukstis, L. A., editors (1990) Methods of Dendrochronology: Applications in the Environmental Sciences. Springer. ISBN13: 9780792305866.
Cook, E. R. (1985). A Time Series Analysis Approach to Tree Ring Standardization. PhD thesis, The University of Arizona.
chron
, crn.plot
,
ar
, arima
library(graphics)
library(utils)
data(co021)
co021.rwi < detrend(rwl = co021, method = "AgeDepSpline")
co021.crn < chron.ars(co021.rwi)
plot(co021.crn,xlab="Year",ylab="RWI",add.spline=TRUE,nyrs=20)
cor(co021.crn)
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