posneg.data {FlexParamCurve} | R Documentation |
Simulated growth of black-browed albatrosses
Description
The posneg.data
data frame has 1300 rows and 3 columns of records of
the simulated masses for black-browed albatross chicks between 0 and 166
days of age.
Usage
posneg.data
Format
This object of class c("nfnGroupedData", "nfGroupedData",
"groupedData", "data.frame")
containing the following columns:
- mass
-
a numeric vector of chick masses (g).
- age
-
a numeric vector of chick ages (days).
- id
-
an ordered factor indicating unique id of each simulated individual, i.e. which data belongs to which individual.
Details
No published parameter estimates with associated variability are available for
positive-negative growth curves. These data were simulated using
an 8-parameter positive-negative Richards curve (SSposnegRichards
(model 1)), using parameters drawn from normal distributions with the following
means (standard deviations):
Asym=4300 (180) K=0.06 (0.01) Infl=23 (0.4) M=0.1 (0.05) RAsym=1433.3 (540) #1/3 of Asym, more variable Rk=0.108 (0.03) #1.8 times faster recession, more variable Ri=Infl+87.259 (1.7) # more variable but linked to Infl RM=M (0.15) #more variable
These values were chosen through comparison of growth curves with Huin and Prince (2000) Fig 2
and variability observed between individual chicks of little penguins in a 10 year dataset
(Chiaradia and Nisbet unpublished data). Each simulated individual had 13 measurements
stratified through the development period, with 1-13 day random differences in timing
of each measurement.
This data object has methods for nlme
grouped-data classes.
Source
Huin, N. & Prince, P.A. (2000) Chick growth in albatrosses: curve fitting with a twist. Journal of Avian Biology, 31, 418-425.
Examples
require(stats); require(graphics)
#view data
posneg.data
#create list for fixed parameters
modpar(posneg.data$age, posneg.data$mass, pn.options = "myoptions")
plot(mass ~ age, data = posneg.data, subset = id == "1",
xlab = "Chick age (day)", las = 1,
ylab = "Chick mass (g)",
main = "posneg.data data and fitted curve (Chick #1 only)")
fm1 <- nls(mass ~ SSposnegRichards(age,Asym=Asym,K=K,Infl=Infl, RAsym=RAsym,
Rk=Rk,Ri=Ri,modno=22, pn.options= "myoptions"),
data = posneg.data, subset = id == "1")
age <- seq(0, 166, length.out = 101)
lines(age, predict(fm1, list(age = age)))