## ----, echo=FALSE, warning=FALSE----------------------------------------- myecho <- TRUE myeval <- TRUE library(knitr) library(DSsim) ## ----packages, echo=myecho, eval=FALSE----------------------------------- ## needed.packages <- c("DSsim", "mrds", "shapefiles", "splancs") ## myrepo <- "http://cran.rstudio.com" ## install.packages(needed.packages, repos=myrepo) ## ----setdir, echo=myecho, eval=myeval------------------------------------ ## ----shapes, echo=myecho, eval=myeval------------------------------------ library(shapefiles) region.shapefile <- read.shapefile("DSsim_study/Region") ## ----makereg, echo=myecho, eval=myeval----------------------------------- region <- make.region(region.name = "Survey Region", units = "m", shapefile = region.shapefile) ## ----plotreg, echo=myecho, eval=myeval----------------------------------- plot(region, plot.units = "km") ## ----othersurf, echo=myecho, eval=FALSE---------------------------------- ## density <- make.density(region = region, x.space = 1000, y.space = 1000, constant = 0.4e-7) ## ## density <- add.hotspot(density, centre = c(-2500, 2224000), sigma = 10000, amplitude = 0.1e-7) ## density <- add.hotspot(density, centre = c(0, 2184000), sigma = 18000, amplitude = -0.5e-8) ## ----loadsurf, echo=myecho, eval=myeval---------------------------------- # premade.surface <- paste(my.directory, "density.surface.robj", sep="/") load("DSsim_study/density.surface.robj") head(density.surface[[1]]) ## ----popden, echo=myecho, eval=myeval------------------------------------ pop.density <- make.density(region = region, density.surface = density.surface, x.space = 1000, y.space = 1000) ## ----viewden, echo=myecho, eval=myeval----------------------------------- plot(pop.density, plot.units = "km") plot(region, add = TRUE) ## ----abund, echo=myecho, eval=myeval------------------------------------- pop.description <- make.population.description(region.obj = region, density.obj = pop.density, N = 1500, fixed.N = TRUE) ## ----truedetect, echo=myecho, eval=myeval-------------------------------- detect <- make.detectability(key.function = "hn", scale.param = 500, truncation = 1000) ## ----subjpath, echo=myecho, eval=myeval---------------------------------- new.directory <- paste(getwd(), "DSsim_study/Survey_Transects/Subjective_Design", sep="/") subjective.design <- make.design(transect.type = "Line", design.details = c("user specified"), region = region, plus.sampling = FALSE, path = new.directory) subjective.design@filenames ## ----candidate.detfns, echo=myecho, eval=myeval-------------------------- ddf.analyses <- make.ddf.analysis.list( dsmodel = list(~cds(key = "hn", formula = ~1), #half-normal model ~cds(key = "hr", formula = ~1)), #hazard-rate model method = "ds", criteria = "AIC") ## ----simobj, echo=myecho, eval=myeval------------------------------------ my.simulation.subjective <- make.simulation(reps = 10, single.transect.set = TRUE, region.obj = region, design.obj = subjective.design, population.description.obj = pop.description, detectability.obj = detect, ddf.analyses.list = ddf.analyses) ## ----simproperties, eval=myeval, echo=myecho----------------------------- #set the display window up for 4 plots par(mfrow = c(2,2)) #generate and plot and example population pop <- generate.population(my.simulation.subjective) plot(region) plot(pop) #generate (or rather load from file) the transects transects <- generate.transects(my.simulation.subjective) plot(region) plot(transects, col = 4, lwd = 2) #simulate the survey process of detection eg.survey <- create.survey.results(my.simulation.subjective) plot(eg.survey) #have a look at the distance data from the simulated survey dist.data <- get.distance.data(eg.survey) head(dist.data) hist(dist.data$distance, xlab = "Distance (m)", main = "Distance Data") par(mfrow=c(1,1)) ## ----runsim, echo=myecho, eval=myeval------------------------------------ my.simulation.subjective.run <- run(my.simulation.subjective) summary(my.simulation.subjective.run)