lnLCF | R Documentation |
Calculate the -log likelihood of data within a model.
lnLCF(x, data, fixed.parameters = NULL, parallel = TRUE, verbose = FALSE)
x |
A named vector of parameters (mu, sd, mu_season, sd_season, a, p and OTN). |
data |
CMR database formated using TableECFOCF(). |
fixed.parameters |
Parameters that are fixed. |
parallel |
If TRUE, parallel computing in ECFOCF_f is used. |
verbose |
if TRUE, show the parameters. |
lnLCF calculate the -log likelihood of data within a model.
Return the -log likelihood of data within a model.
Marc Girondot
Other Model of Clutch Frequency:
ECFOCF_f()
,
ECFOCF_full()
,
TableECFOCF()
,
fitCF()
,
fitCF_MHmcmc()
,
fitCF_MHmcmc_p()
,
generateCF()
,
logLik.ECFOCF()
,
plot.ECFOCF()
,
plot.TableECFOCF()
## Not run:
library(phenology)
# Example
ECFOCF_2002 <- TableECFOCF(MarineTurtles_2002)
lnLCF(x=c(mu=4.71768454279272,
sd=1.075711951667,
p=-1.79746277312909),
data=ECFOCF_2002)
ECFOCF_2002 <- TableECFOCF(MarineTurtles_2002, date0=as.Date("2002-01-01"))
fp <- rep(0, dim(ECFOCF_2002)[3])
names(fp) <- paste0("p.", formatC(1:(dim(ECFOCF_2002)[3]), width=2, flag="0"))
par <- c(mu1 = 0.6404831115214353,
sd1 = 0.69362774786433479,
mu2 = 5.6404831115214353,
sd2 = 5.69362774786433479,
mu_season = 12.6404831115214353,
sd_season = 1.69362774786433479,
OTN=1)
par <- c(par, fp[attributes(ECFOCF_2002)$table["begin"]:attributes(ECFOCF_2002)$table["final"]])
fixed.parameters <- c(p=-Inf)
lnLCF(x=par, data=ECFOCF_2002, fixed.parameters=fixed.parameters)
## End(Not run)
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