chillR (version 0.75)

phenologyFitter: phenologyFitter

Description

phenologyFitter

Usage

phenologyFitter(
  par.guess = NULL,
  modelfn = PhenoFlex_GDHwrapper,
  bloomJDays,
  SeasonList,
  control = list(smooth = FALSE, verbose = TRUE, maxit = 1000, nb.stop.improvement = 250),
  lower,
  upper,
  seed = 1235433,
  ...
)

Value

an object of class `phenologyFit`. It contains the named elements `model_fit` with the returned object from GenSA, `par` the best fit parameters, `pbloomJDays` the predicted bloom JDays and the inputs `par.guess`, `modelfn`, `bloomJDays`, `lower`, `upper`, `control`, `SeasonList` and `...`.

Arguments

par.guess

numeric vector. Initial guesses for fit parameters. This can be set to `NULL`, in which case `GenSA` choses initial parameters.

modelfn

function. Model function which computes the index in `temperatures` at which blooming occures. It must have as first argument a data frame with at least the two columns `Temp` and `JDays` for one season, see `SeasonList`. It can have further arguments which can be passed via `...`. The `modelfn` must return a single numeric value for the predicted bloom JDay for that season. `NA` is an allowed return value if no blooming occures in that season. The default is the PhenoFlex with GDH as heat accumulation. Alternative is PhenoFlex_GAUSSwrapper with GAUSSian heat accumulation. But this function can also be user defined.

bloomJDays

integer vector. vector of observed bloom JDays per year

SeasonList

list. Must be a list of data frames, each data frame for one season. Each data.frame must at least have a column `Temp` with the temperature vector and `JDays` with the corresponding JDay vector. Can be generated by e.g. genSeasonList. `length(SeasonList)` must be equal to `length(bloomJDays)`.

control

control parameters to `GenSA`, see `GenSA::GenSA`

lower

Vector with length of ‘par.guess’. Lower bounds for components.

upper

Vector with length of ‘par.guess’. Upper bounds for components.

seed

integer seed for the random number generator used by `GenSA`.

...

further parameters to be passed on to `modelfn`.

Author

Carsten Urbach <[e-mail]>

Examples

## this example does not make sense as a fit, but demonstrates
## how to use `phenologyFitter`
data(KA_weather)
data(KA_bloom)
hourtemps <- stack_hourly_temps(KA_weather, latitude=50.4)
SeasonList <- genSeasonList(hourtemps$hourtemps, years=c(2007,2008))
par <- c(40, 190, 0.5, 25, 3372.8, 9900.3, 6319.5, 5.939917e13, 4, 36, 4, 1.6)
upper <- c(41, 200, 1, 30, 4000, 10000, 7000, 6.e13, 10, 40, 10, 50)
lower <- c(38, 180, 0.1, 0, 3000, 9000, 6000, 5.e13, 0, 0, 0, 0.05)
X <- phenologyFitter(par.guess=par, bloomJDays=KA_bloom$pheno[c(24,25)], 
  SeasonList=SeasonList, lower=lower, upper=upper,
  control=list(smooth=FALSE, verbose=TRUE, maxit=10, nb.stop.improvement=5))
summary(X)
plot(X)