modelFrame {BIOdry} | R Documentation |
Dendroclimatic-fluctuations modeling
Description
This function develops recursive evaluation of functions for one-level modeling (FOLM) and LME detrending of dendroclimatic chronologies.
Usage
modelFrame(rd, fn = list("rtimes",
"scacum", "amod"),
lv = list(2, 1, 1),
form = "tdForm",
...)
Arguments
rd |
|
fn |
|
lv |
|
form |
|
... |
Further arguments in |
Details
Defaults model fluctuations in
tree-ring width chronologies via recursive
implementation of four FOLM:
rtimes
, scacum
,
amod
, and
frametoLme
. Nevertheless,
other FOLM can be implemented to model
aridity-index fluctuations(see example with
climatic data). Processed chronologies are
detrended with lme
function
and other nlme
methods
. Internal algorithm uses
shiftFrame
arguSelect
and
ringApply
functions. Consequently, arguments that are
not iterated over factor-level labels in the
processed data are specified in 'MoreArgs'
lists (see examples). Arguments in
modelFrame
objects can be updated
with update
function.
Value
Threefold list with fluctuations in fluc
,
groupedData object in model
, and model call in
call
.
Author(s)
Wilson Lara <wilarhen@gmail.com> [aut, cre] (<https://orcid.org/0000-0003-3527-1380>), Felipe Bravo <fbravo@pvs.uva.es> [aut] (<https://orcid.org/0000-0001-7348-6695>)
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
##TRW chronology (mm) and inside-bark radii
data(Pchron,envir = environment())
## Parameters of allometric model to compute Diameter at Breast
## Height over bark (DBH, cm) from diameter inside bark (dib, cm)
## and Total Tree Biomass (TTB, kg tree -1 ) from DBH (Lara
## et. al. 2013):
biom_param <- c(2.87, 0.85, 0.05, 2.5)
## Modeling tree-biomass fluctuations while accounting for
## within-plot source variability (see defaults in "modelFrame"
## function)
## \donttest{
## trwf <- modelFrame(Pchron,
## to = 'cm',
## MoreArgs = list(mp = c(2,1, biom_param)),
## log.t = FALSE,
## on.time = FALSE)
## }
## Climatic records:
data(Temp,envir = environment())
data(Prec,envir = environment())
## Aridity-index fluctuations:
## \donttest{
## aif <- modelFrame(rd = list(Prec, Temp),
## fn = list('moveYr','wlai'),
## lv = list('year','year'),
## form = 'lmeForm')
## summary(aif$'model')
## }