## Not run: ------------------------------------
#
# ## commands used to create ovenCH from the input files
# ## "netsites0509.txt" and "ovencapt.txt"
# ## for information only - these files not distributed
# netsites0509 <- read.traps(file = "netsites0509.txt",
# skip = 1, detector = "proximity")
# temp <- read.table("ovencapt.txt", colClasses=c("character",
# "character", "numeric", "numeric", "character"))
# ovenCHp <- make.capthist(temp, netsites0509, covnames=c("Sex"))
# ovenCHp <- updateCH(ovenCHp) # drop repeat detections
## ---------------------------------------------
par(mfrow = c(1,5), mar = c(1,1,4,1))
plot(ovenCHp, tracks = TRUE, varycol = TRUE)
par(mfrow = c(1,1), mar = c(5,4,4,2) + 0.1) ## defaults
counts(ovenCHp, "n")
## Not run: ------------------------------------
# ## trimmed version of data - for consistency with earlier versions
#
# ovenCH <- reduce(ovenCHp, outputdetector = "multi", dropunused = FALSE)
#
# ## array constant over years, so build mask only once
# ovenmask <- make.mask(traps(ovenCH)[["2005"]], type="pdot", buffer=400,
# spacing=15, detectpar=list(g0=0.03, sigma=90), nocc=10)
#
# ## fit constant-density model
# ovenbird.model.1 <- secr.fit(ovenCH, mask = ovenmask)
# ovenbird.model.1
#
# ## fit net avoidance model
# ovenbird.model.1b <- secr.fit(ovenCH, mask = ovenmask, model =
# list(g0~b))
# ovenbird.model.1b
#
# ## fit model with time trend in detection
# ovenbird.model.1T <- secr.fit(ovenCH, mask = ovenmask, model =
# list(g0 ~ T))
# ovenbird.model.1T
#
# ## fit model with 2-class mixture for g0
# ovenbird.model.h2 <- secr.fit(ovenCH, mask = ovenmask, model =
# list(g0~h2))
# ovenbird.model.h2
#
## ---------------------------------------------
## compare & average pre-fitted models
AIC (ovenbird.model.1, ovenbird.model.1b, ovenbird.model.1T,
ovenbird.model.h2)
model.average (ovenbird.model.1,ovenbird.model.1b, ovenbird.model.1T,
ovenbird.model.h2, realnames = "D")
## select one year to plot
plot(ovenbird.model.1b, newdata = data.frame(session = "2005",
b = 0))
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