R: Bin distance data

formatDistData {unmarked} | R Documentation

## Bin distance data

### Description

Convert individual-level distance data to the transect-level format required by `distsamp` or `gdistsamp`

### Usage

    formatDistData(distData, distCol, transectNameCol, dist.breaks,
                          occasionCol, effortMatrix)

### Arguments

`distData` | data.frame where each row is a detected individual. Must have at least 2 columns. One for distances and the other for transect names.
`distCol` | character, name of the column in distData that contains the distances. The distances should be numeric.
`transectNameCol` | character, column name containing transect names. The transect column should be a factor.
`dist.breaks` | numeric vector of distance interval cutpoints. Length must equal J+1.
`occasionCol` | optional character. If transects were visited more than once, this can be used to format data for `gdistsamp`. It is the name of the column in distData that contains the occasion numbers. The occasion column should be a factor.
`effortMatrix` | optional matrix of 1 and 0s that is M * J in size and will allow for the insertion of NAs where the matrix = 0, indicating that a survey was not completed. When not supplied a matrix of all 1s is created since it is assumed all surveys were completed.

### Details

This function creates a site (M) by distance interval (J) response matrix from a data.frame containing the detection distances for each individual and the transect names. Alternatively, if each transect was surveyed T times, the resulting matrix is M x JT, which is the format required by `gdistsamp`, see`unmarkedFrameGDS`.

### Value

An M x J or M x JT matrix containing the binned distance data. Transect names will become rownames and colnames will describe the distance intervals.

### Note

It is important that the factor containing transect names includes levels for all the transects surveyed, not just those with >=1 detection. Likewise, if transects were visited more than once, the factor containing the occasion numbers should include levels for all occasions. See the example for how to add levels to a factor.

### See Also

`distsamp`, `unmarkedFrame`

### Examples

    # Create a data.frame containing distances of animals detected
    # along 4 transects.
    dat <- data.frame(transect=gl(4,5, labels=letters[1:4]),
                      distance=rpois(20, 10))
    dat

    # Look at your transect names.
    levels(dat$transect)

    # Suppose that you also surveyed a transect named "e" where no animals were
    # detected. You must add it to the levels of dat$transect
    levels(dat$transect) <- c(levels(dat$transect), "e")
    levels(dat$transect)

    # Distance cut points defining distance intervals
    cp <- c(0, 8, 10, 12, 14, 18)

    # Create formated response matrix
    yDat <- formatDistData(dat, "distance", "transect", cp)
    yDat

    # Now you could merge yDat with transect-level covariates and
    # then use unmarkedFrameDS to prepare data for distsamp

    ## Example for data from multiple occasions

    dat2 <- data.frame(distance=1:100, site=gl(5, 20),
                       visit=factor(rep(1:4, each=5)))
    cutpt <- seq(0, 100, by=25)
    y2 <- formatDistData(dat2, "distance", "site", cutpt, "visit")
    umf <- unmarkedFrameGDS(y=y2, numPrimary=4, survey="point",
                            dist.breaks=cutpt, unitsIn="m")
     ## Example for datda from multiple occasions with effortMatrix

     dat3 <-  data.frame(distance=1:100, site=gl(5, 20), visit=factor(rep(1:4, each=5)))
     cutpt <- seq(0, 100, by=25)

     effortMatrix <- matrix(ncol=4, nrow=5, rbinom(20,1,0.8))

     y3 <- formatDistData(dat2, "distance", "site", cutpt, "visit", effortMatrix)

[Package unmarked version 1.0.0 Index]