correlation.function: Performs correlations functions

In dplRCon: Concordance for Dendroclimatology

Description

Uses the imported climate variables and tree ring data to produce seasonal correlation functions. Also, uses the bootstrapped chronologies to produce confidence intervals.

Usage

correlation.function(climate.anom.season.data, site.chron.data, site.boot.data,
  period.RF, col.names.season, Climate.name, Subset.name)

Arguments

climate.anom.season.data	climate data anomalies for seasons
site.chron.data	site chronologies, matrix: rows=year, col=subset.1, subset.2,fullest
site.boot.data	bootstrapped site chronologies, list: matrices for each subset with: row=year, col=bootstrapped series
period.RF	the period used to calculate response functions, vector: (start,end)
col.names.season	col.names.season<- list("SON_2", "DJF_2", "MAM_2", "JJA_2", "SON_1", "DJF_1", "MAM_1", "JJA_1", "SON", "DJF", "MAM", "JJA")
Climate.name	name of the climate variable for which correlation functions are being calculated
Subset.name	names given to each of the subsets.

Value

corr.site.1	The correlations between the climate variable and the site chronology for the 1st subset.
corr.site.2	The correlations between the climate variable and the site chronology for the 12st subset.
percentile.ci.1	The percentile confidence intervals for the 1st subset.
percentile.ci.2	The percentile confidence intervals for the 2st subset.

Other summary varibles

summary.ci.1
summary.ci.2
t.mean	Test for correlation equal zero
t.meanequal	Test for correlations from the two subsets are equal
percentile.ci

Note

site.chron.data, and site.boot.data must be in the same order and confidence intervals plotted are for the 1st two subsets.

Examples

## Not run: 
period.RF<-c(1900,1990)
col.names.season <- list("SON_2", "DJF_2", "MAM_2", "JJA_2", "SON_1", "DJF_1", "MAM_1","JJA_1",
         "SON", "DJF", "MAM", "JJA")
##  Full dataset
site.full <- site.chron(spline200.sub0.2000.n$sub.series.stand, aver.by.tree=F)
site.chron.data <- cbind(site.full$aver.site, site.full$aver.site)
site.boot.full <- ts(boot.full$boot.series.mean, start=tsp(site.full$aver.site)[1] )
site.boot.data<-list(site.boot.full, site.boot.full)

corr.SOI.full<-correlation.function(SOI.anom.season.data, site.chron.data,site.boot.data,
      period.RF, col.names.season,
      Climate.name="SOI", Subset.name=c("0-20cm","20-200cm" ) )
corr.prec.full<-correlation.function(prec.anom.season.data, site.chron.data,site.boot.data,
     period.RF, col.names.season,
     Climate.name="SOI", Subset.name=c("0-20cm","20-200cm" ) )
corr.temp.full<-correlation.function(temp.anom.season.data, site.chron.data,site.boot.data,
     period.RF, col.names.season,
     Climate.name="SOI", Subset.name=c("0-20cm","20-200cm" ) )

##	Near vs Far
site.0.20  <- site.chron(spline200.sub0.20.n$sub.series.stand, aver.by.tree=F)
site.20.200 <- site.chron(spline200.sub20.2000.n$sub.series.stand, aver.by.tree=F)
site.chron.data <- cbind(site.0.20$aver.site, site.20.200$aver.site)

site.boot.0.20 <- ts(boot.0.20$boot.series.mean, start=tsp(site.0.20$aver.site)[1] )
site.boot.20.200 <- ts(boot.20.2000$boot.series.mean, start=tsp(site.20.200$aver.site)[1] )
site.boot.data<-list(site.boot.0.20, site.boot.20.200)

corr.SOI<-correlation.function(SOI.anom.season.data, site.chron.data, site.boot.data,
   period.RF, col.names.season,
   Climate.name="SOI",Subset.name=c("0-20cm","20-200cm" ) )
corr.prec<-correlation.function(prec.anom.season.data, site.chron.data,          site.boot.data,
   period.RF, col.names.season,
   Climate.name="SOI", Subset.name=c("0-20cm","20-200cm" ) )
corr.temp<-correlation.function(temp.anom.season.data, site.chron.data, site.boot.data,
   period.RF, col.names.season,
   Climate.name="SOI", Subset.name=c("0-20cm","20-200cm" ) )

## End(Not run)

dplRCon documentation built on May 2, 2019, 2:02 p.m.