plot.fitRMU: Plot the synthesis of RMU fit.
| plot.fitRMU | R Documentation |
Plot the synthesis of RMU fit.
Description
The function plot.fitRMU plots the results of fitRMU().
In most of the cases, replicate.CI can be set to 0 for what="proportions" or "numbers".
The parameter CI.RMU can be used when this function is used several times with the same data.
Usage
## S3 method for class 'fitRMU'
plot(
x,
...,
resultMCMC = NULL,
chain = 1,
replicate.CI = 10000,
CI.RMU = NULL,
what = "proportions",
criteria = "50%",
aggregate = "both",
order = NULL,
control.legend = list(),
show.legend = TRUE,
col = rainbow,
border = NA,
names.legend = NULL
)
Arguments
x |
A result file generated by fitRMU |
... |
Parameters used by plot |
resultMCMC |
MCMC result for fitRUM |
chain |
Chain to be plotted for MCMC |
replicate.CI |
Number of replicates to estimate CI |
CI.RMU |
A result of CI.RMU() |
what |
Can be proportions, numbers or total |
criteria |
What criteria will be used for proportions or numbers: mean or 50% |
aggregate |
Can be model or both |
order |
Give the order of series in plot, from bottom to top. Can be used to not show series. |
control.legend |
Parameters send to legend |
show.legend |
If FALSE, does not show legend |
col |
The function used to generate colors. |
border |
The border of polygons used to represent the proportions. |
names.legend |
Names to show in legend. |
Details
plot.fitRMU plots the results of a fit RMU.
Value
Return A list with result of CI.RMU()
Author(s)
Marc Girondot
See Also
Other Fill gaps in RMU:
CI.RMU(),
fitRMU(),
fitRMU_MHmcmc(),
fitRMU_MHmcmc_p(),
logLik.fitRMU()
Examples
## Not run:
library("phenology")
RMU.names.AtlanticW <- data.frame(mean=c("Yalimapo.French.Guiana",
"Galibi.Suriname",
"Irakumpapy.French.Guiana"),
se=c("se_Yalimapo.French.Guiana",
"se_Galibi.Suriname",
"se_Irakumpapy.French.Guiana"), stringsAsFactors = FALSE)
data.AtlanticW <- data.frame(Year=c(1990:2000),
Yalimapo.French.Guiana=c(2076, 2765, 2890, 2678, NA,
6542, 5678, 1243, NA, 1566, 1566),
se_Yalimapo.French.Guiana=c(123.2, 27.7, 62.5, 126, NA,
230, 129, 167, NA, 145, 20),
Galibi.Suriname=c(276, 275, 290, NA, 267,
542, 678, NA, 243, 156, 123),
se_Galibi.Suriname=c(22.3, 34.2, 23.2, NA, 23.2,
4.3, 2.3, NA, 10.3, 10.1, 8.9),
Irakumpapy.French.Guiana=c(1076, 1765, 1390, 1678, NA,
3542, 2678, 243, NA, 566, 566),
se_Irakumpapy.French.Guiana=c(23.2, 29.7, 22.5, 226, NA,
130, 29, 67, NA, 15, 20), stringsAsFactors = FALSE)
cst <- fitRMU(RMU.data=data.AtlanticW, RMU.names=RMU.names.AtlanticW,
colname.year="Year", model.trend="Constant",
model.SD="Zero")
expo <- fitRMU(RMU.data=data.AtlanticW, RMU.names=RMU.names.AtlanticW,
colname.year="Year", model.trend="Exponential",
model.SD="Zero")
YS <- fitRMU(RMU.data=data.AtlanticW, RMU.names=RMU.names.AtlanticW,
colname.year="Year", model.trend="Year-specific",
model.SD="Zero")
YS1 <- fitRMU(RMU.data=data.AtlanticW, RMU.names=RMU.names.AtlanticW,
colname.year="Year", model.trend="Year-specific",
model.SD="Zero", model.rookeries="First-order")
YS1_cst <- fitRMU(RMU.data=data.AtlanticW, RMU.names=RMU.names.AtlanticW,
colname.year="Year", model.trend="Year-specific",
model.SD="Constant", model.rookeries="First-order",
parameters=YS1$par)
YS2 <- fitRMU(RMU.data=data.AtlanticW, RMU.names=RMU.names.AtlanticW,
colname.year="Year", model.trend="Year-specific",
model.SD="Zero", model.rookeries="Second-order",
parameters=YS1$par)
YS2_cst <- fitRMU(RMU.data=data.AtlanticW, RMU.names=RMU.names.AtlanticW,
colname.year="Year", model.trend="Year-specific",
model.SD="Constant", model.rookeries="Second-order",
parameters=YS1_cst$par)
compare_AIC(Constant=cst, Exponential=expo,
YearSpecific=YS)
compare_AIC(YearSpecific_ProportionsFirstOrder_Zero=YS1,
YearSpecific_ProportionsFirstOrder_Constant=YS1_cst)
compare_AIC(YearSpecific_ProportionsConstant=YS,
YearSpecific_ProportionsFirstOrder=YS1,
YearSpecific_ProportionsSecondOrder=YS2)
compare_AIC(YearSpecific_ProportionsFirstOrder=YS1_cst,
YearSpecific_ProportionsSecondOrder=YS2_cst)
barplot_errbar(YS1_cst$proportions[1, ], y.plus = YS1_cst$proportions.CI.0.95[1, ],
y.minus = YS1_cst$proportions.CI.0.05[1, ], las=1, ylim=c(0, 0.7),
main="Proportion of the different rookeries in the region")
plot(cst, main="Use of different beaches along the time", what="total")
plot(expo, main="Use of different beaches along the time", what="total")
plot(YS2_cst, main="Use of different beaches along the time", what="total")
plot(YS1, main="Use of different beaches along the time")
plot(YS1_cst, main="Use of different beaches along the time")
plot(YS1_cst, main="Use of different beaches along the time", what="numbers")
parpre <- par(mar=c(4, 4, 2, 5)+0.4)
par(xpd=TRUE)
plot(YS, main="Use of different beaches along the time",
control.legend=list(x=2000, y=0.4, legend=c("Yalimapo", "Galibi", "Irakumpapy")))
par(mar=parpre)
# Example to modify order of series
plot(cst, order=c("Galibi.Suriname", "Irakumpapy.French.Guiana"))
plot(cst, order=c("Galibi.Suriname", "Irakumpapy.French.Guiana", "Yalimapo.French.Guiana"))
# Example to change the color
plot(cst, order=c("Galibi.Suriname", "Irakumpapy.French.Guiana", "Yalimapo.French.Guiana"),
col=function(n) rep(c("gray", "lightgrey"), floor(n/2)), border="black",
names.legend=c("Yalimapo", "Galibi", "Irakumpapy"))
## End(Not run)
