plot.ECFOCF: Plot a result of clutch frequency fit.

View source: R/plot.ECFOCF.R

plot.ECFOCFR Documentation

Plot a result of clutch frequency fit.


This function plots the result of fitCF().
The result data plots the observed ECF-OCF table.
The result dataOCF plots the observed OCF table.
The result dataECF plots the observed ECF table.
The result CF plots the true clutch frequency.
The result OCF plots the observed clutch frequency.
The result ECF plots the estimated clutch frequency.
The result ECFOCF plots the bivariate observed vs. estimated clutch frequency.
The result ECFOCF0 plots the bivariate observed vs. estimated clutch frequency without the 0 OCF.
The result prob plots the probabilities of capture.
The result period plots the probabilities of nesting according to period.
If category is left to NA, the compound value for all the population is plotted.
When result="data" is used, this is a parser for plot.TableECFOCF().
See this function for the parameters.
The parameter y.axis is the shift of the x legends for result="prob".
When a resultMCMC is indicated, if replicates is "all", all values are used; if a value lower than number of iterations is indicated, a regular thinning is used and if a value larger then number if iteration is indicated, a sampling with replacement is used.


## S3 method for class 'ECFOCF'
  result = "CF",
  category = NA,
  period = 1,
  resultMCMC = NULL,
  chain = 1,
  replicates = "all"



A result for fitCF().


Graphic parameters, see plot.TableECFOCF() or par.


What result will be plotted: data, dataOCF, dataECF, ECF, OCF, ECFOCF, ECFOCF0, CF, Prob, period


What category will be plotted, numeric or NA for all.


The period that will be plotted.


A result from fitRMU_MHmcmc.


Which chain to be used in resultMCMC.


How many replicates fron resultMCMC.


plot.ECFOCF plots a result of clutch frequency fit.




Marc Girondot

See Also

Other Model of Clutch Frequency: ECFOCF_full(), ECFOCF_f(), TableECFOCF(), fitCF_MHmcmc_p(), fitCF_MHmcmc(), fitCF(), generateCF(), lnLCF(), logLik.ECFOCF(), plot.TableECFOCF()


## Not run: 
# Example
ECFOCF_2002 <- TableECFOCF(MarineTurtles_2002)
o_mu1p2_NB <- fitCF(x = c(mu = 4.6426989650675701, 
                         sd = 75.828239144717074, 
                         p1 = 0.62036295627161053,
                         p2 = -2.3923021862881511, 
                         OTN = 0.33107456308054345),
par(mar=c(4, 4, 1, 1)+0.4)
plot(o_mu1p2_NB, result="data", category=NA, 
     bty="n", las=1, cex.points=3, cex.axis = 0.8)
plot(o_mu1p2_NB,result="data", category=NA, 
     bty="n", las=1, cex.points=3, pch=NA, 
     col.labels = "red", show.labels=TRUE, cex.0=0.2, 
     show.0 = TRUE, col.0="blue", pch.0=4)
plot(o_mu1p2_NB, result="dataOCF", category=NA, 
     bty="n", las=1)
plot(o_mu1p2_NB, result="dataECF", category=NA, 
     bty="n", las=1)
plot(o_mu1p2_NB, result="CF", bty="n", las=1)

plot(o_mu1p2_NB, result="OCF", category=1, bty="n", las=1)
plot(o_mu1p2_NB, result="OCF", category=2, bty="n", las=1)

plot(o_mu1p2_NB, result="ECFOCF", bty="n", las=1)

plot(o_mu1p2_NB, result="ECFOCF0", bty="n", las=1)
plot(o_mu1p2_NB, result="ECFOCF0", category=1, bty="n", las=1)
plot(o_mu1p2_NB, result="ECFOCF0", category=2, bty="n", las=1)

plot(o_mu1p2_NB, result="Prob", category=c(1, 2), bty="n", las=1)
plot(o_mu1p2_NB, result="Prob", category=c(2, 1), bty="n", las=1)

## End(Not run)

phenology documentation built on Oct. 16, 2023, 9:06 a.m.