View source: R/HatchingSuccess.predict.R
predict.HatchingSuccess | R Documentation |
Set of functions to study the hatching success.
If replicates is 0, it returns only the fitted model.
If replicates is null and resultmcmc is not null, it will use all the mcmc data.
if replicates is lower than the number of iterations in resultmcmc, it will use sequence of data regularly thined.
## S3 method for class 'HatchingSuccess'
predict(
object,
...,
temperature = NULL,
probs = c(0.025, 0.5, 0.975),
replicates = NULL,
resultmcmc = NULL,
chain = 1
)
object |
The return of a fit done with HatchingSuccess.fit(). |
... |
Not used |
temperature |
A vector of temperatures. |
probs |
Quantiles. |
replicates |
Number of replicates to estimate the confidence interval. |
resultmcmc |
Results obtained using HatchingSuccess.MHmcmc() |
chain |
Chain to use in resultmcmc |
predict.HatchingSuccess returns prediction based on a model fitted with HatchingSuccessfit()
Return a matrix with prediction based on a model fitted with HatchingSuccess.fit()
Marc Girondot
Other Hatching success:
HatchingSuccess.MHmcmc()
,
HatchingSuccess.MHmcmc_p()
,
HatchingSuccess.fit()
,
HatchingSuccess.lnL()
,
HatchingSuccess.model()
,
logLik.HatchingSuccess()
,
nobs.HatchingSuccess()
## Not run:
library(embryogrowth)
totalIncubation_Cc <- subset(DatabaseTSD,
Species=="Caretta caretta" &
Note != "Sinusoidal pattern" &
!is.na(Total) & Total != 0)
par <- c(S.low=0.5, S.high=0.3,
P.low=25, deltaP=10, MaxHS=0.8)
HatchingSuccess.lnL(x=par, data=totalIncubation_Cc)
g <- HatchingSuccess.fit(par=par, data=totalIncubation_Cc)
HatchingSuccess.lnL(par=g$par, data=totalIncubation_Cc)
plot(g)
## End(Not run)
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