BIOdry (version 0.3)

ringApply: Multilevel apply

Description

Wrapper of Map to apply functions on multilevel data frames and preserve factor-level structure in the outputs.

Usage

ringApply(rd, lv = 1, fn = "scacum", ...)

Arguments

rd

data.frame object with factor-level columns.

lv

numeric position, or character name, of a factor-level column in the data frame.

fn

character name of the function to be evaluated (see details). Default 'scacum' computes scaled-cummulative radii.

...

Further arguments in fn (see details)

Value

object preserving initial factor-level columns.

Details

Other functions such as rtimes, scacum, amod, or wlai can be implemented. Function arguments should be formulated as suggested in mapply, with no vectorized arguments being stored in a MoreArgs list.

References

Lara, W., F. Bravo, D. Maguire. 2013. Modeling patterns between drought and tree biomass growth from dendrochronological data: A multilevel approach. Agric. For. Meteorol., 178-179:140-151.

Examples

##Multilevel data frame of tree-ring widths:
data(Prings05,envir = environment())
## Radial increments measured on 2003:
data(Pradii03,envir = environment())    
## Monthly precipitation sums and average temperatures:
data(PTclim05,envir = environment())

##synchronized times by tree with 'rtimes':
dfm1 <- ringApply(Prings05,lv = 2,fn = 'rtimes')
str(dfm1)
##some synchronized times from time 1 to time 9:
subset(dfm1,time%in%c(1:9,NA))

## Cummulative radial increments by sample:
dfm2 <- ringApply(dfm1,lv = 'sample',y = Pradii03,fn = 'scacum')
str(dfm2)    
##Allometric modeling by sample:
dfm3 <- ringApply(dfm2,lv = 'sample',fn = 'amod',
                  MoreArgs = list(mp = c(1,1,0.25 * pi,2),
                                  un = c('mm','m')))
str(dfm3)

## seasonal years from 'October' to 'September':
cl1 <- ringApply(PTclim05,lv = 'year',fn = 'moveYr')
##using ringApply to compute multilevel aridity indexes with
##function 'wlai':
tail(cl1,15)
wl <- ringApply(cl1,lv = 'year',fn = 'wlai')
str(wl)#only yearly levels with 12 months are evaluated 

## A plot of the computed fluctuations of aridity
d <- groupedData(lmeForm(wl),wl)
plot(d)