stake77 {mrds}

Wooden stake data from 1977 survey

Description

Multiple surveys by different observers of a single 1km transect containing 150 wooden stakes placed randomly throughout a 40 m strip (20m on either side).

Format

A data frame with 150 observations on the following 10 variables.

StakeNo

unique number for each stake 1-150

PD

perpendicular distance at which the stake was placed from the line

Obs1

0/1 whether missed/seen by observer 1

Obs2

0/1 whether missed/seen by observer 2

Obs3

0/1 whether missed/seen by observer 3

Obs4

0/1 whether missed/seen by observer 4

Obs5

0/1 whether missed/seen by observer 5

Obs6

0/1 whether missed/seen by observer 6

Obs7

0/1 whether missed/seen by observer 7

Obs8

0/1 whether missed/seen by observer 8

Source

Laake, J. 1978. Line transect estimators robust to animal movement. M.S. Thesis. Utah State University, Logan, Utah. 55p.

References

Burnham, K. P., D. R. Anderson, and J. L. Laake. 1980. Estimation of Density from Line Transect Sampling of Biological Populations. Wildlife Monographs:7-202.

Examples

data(stake77)
# Extract functions for stake data and put in the mrds format
extract.stake <- function(stake,obs){
  extract.obs <- function(obs){
    example <- subset(stake,eval(parse(text=paste("Obs",obs,"==1",sep=""))),
                      select="PD")
    example$distance <- example$PD
    example$object <- 1:nrow(example)
    example$PD <- NULL
    return(example)
  }
  if(obs!="all"){
    return(extract.obs(obs=obs))
  }else{
    example <- NULL
    for(i in 1:(ncol(stake)-2)){
      df <- extract.obs(obs=i)
      df$person <- i
      example <- rbind(example,df)
    }
    example$person <- factor(example$person)
    example$object <- 1:nrow(example)
    return(example)
  }
}
extract.stake.pairs <- function(stake,obs1,obs2,removal=FALSE){
  obs1 <- paste("Obs",obs1,sep="")
  obs2 <- paste("Obs",obs2,sep="")
  example <- subset(stake,eval(parse(text=paste(obs1,"==1 |",obs2,"==1 ",
                                       sep=""))),select=c("PD",obs1,obs2))
  names(example) <- c("distance","obs1","obs2")
  detected <- c(example$obs1,example$obs2)
  example <- data.frame(object   = rep(1:nrow(example),2),
                        distance = rep(example$distance,2),
                        detected = detected,
                        observer = c(rep(1,nrow(example)),
                                     rep(2,nrow(example))))
  if(removal) example$detected[example$observer==2] <- 1
  return(example)
}
# extract data for observer 1 and fit a single observer model
stakes <- extract.stake(stake77,1)
ds.model <- ddf(dsmodel = ~mcds(key = "hn", formula = ~1), data = stakes,
                method = "ds", meta.data = list(width = 20))
plot(ds.model,breaks=seq(0,20,2),showpoints=TRUE)
ddf.gof(ds.model)

# extract data from observers 1 and 3 and fit an io model
stkpairs <- extract.stake.pairs(stake77,1,3,removal=FALSE)
io.model <- ddf(dsmodel = ~mcds(key = "hn", formula=~1),
                mrmodel=~glm(formula=~distance),
                data = stkpairs, method = "io")
summary(io.model)
par(mfrow=c(3,2))
plot(io.model,breaks=seq(0,20,2),showpoints=TRUE,new=FALSE)
dev.new()
ddf.gof(io.model)