View source: R/HatchingSuccess.lnL.R
HatchingSuccess.lnL | R Documentation |
Set of functions to study the hatching success.
HatchingSuccess.lnL(
par,
data,
fixed.parameters = NULL,
column.Incubation.temperature = "Incubation.temperature",
column.Hatched = "Hatched",
column.NotHatched = "NotHatched"
)
par |
A set of parameters. |
data |
A dataset in a data.frame with a least three columns: Incubation.temperature, Hatched and NotHatched |
fixed.parameters |
A set of parameters that must not be fitted. |
column.Incubation.temperature |
Name of the column with incubation temperatures |
column.Hatched |
Name of the column with hatched number |
column.NotHatched |
Name of the column with not hatched number |
HatchingSuccess.lnL return -log likelihood of the data and the parameters
Return -log likelihood of the data and the parameters
Marc Girondot
Other Hatching success:
HatchingSuccess.MHmcmc()
,
HatchingSuccess.MHmcmc_p()
,
HatchingSuccess.fit()
,
HatchingSuccess.model()
,
logLik.HatchingSuccess()
,
nobs.HatchingSuccess()
,
predict.HatchingSuccess()
## Not run:
library(embryogrowth)
totalIncubation_Cc <- subset(DatabaseTSD,
Species=="Caretta caretta" &
Note != "Sinusoidal pattern" &
!is.na(Total) & Total != 0 &
!is.na(NotHatched) & !is.na(Hatched))
par <- c(S.low=0.5, S.high=0.3,
P.low=25, deltaP=10, MaxHS=0.8)
HatchingSuccess.lnL(par=par, data=totalIncubation_Cc)
g <- HatchingSuccess.fit(par=par, data=totalIncubation_Cc)
HatchingSuccess.lnL(par=g$par, data=totalIncubation_Cc)
t <- seq(from=20, to=40, by=0.1)
CIq <- predict(g, temperature=t)
par(mar=c(4, 4, 1, 1), +0.4)
plot(g)
## End(Not run)
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