R: Create an unmarkedFrameOccuTTD object for the...

unmarkedFrameOccuTTD {unmarked} | R Documentation

## Create an unmarkedFrameOccuTTD object for the time-to-detection model fit by occuTTD

### Description

Organizes time-to-detection occupancy data along with covariates. This S4 class is required by the data argument of `occuTTD`

### Usage

      unmarkedFrameOccuTTD(y, surveyLength, siteCovs=NULL, obsCovs=NULL,
                               numPrimary=1, yearlySiteCovs=NULL)

### Arguments

`y` | An MxR matrix of multi-state occupancy data for a species, where M is the number of sites and R is the maximum number of observations per site (across all primary periods and observations, if you have multi-season data). Values in `y` should be positive.
`surveyLength` | The maximum length of a survey, in the same units as `y`. You can provide either a single value (if all surveys had the same max length), or a matrix matching the dimensions of `y` (if surveys had different max lengths).
`siteCovs` | A `data.frame` of covariates that vary at the site level. This should have M rows and one column per covariate
`obsCovs` | Either a named list of `data.frame`s of covariates that vary within sites, or a `data.frame` with MxR rows in the ordered by site-observation (if single-season) or site-primary period-observation (if multi-season).
`numPrimary` | Number of primary time periods (e.g. seasons) for the dynamic or multi-season version of the model. There should be an equal number of secondary periods in each primary period.
`yearlySiteCovs` | A data frame with one column per covariate that varies among sites and primary periods (e.g. years). It should have MxT rows where M is the number of sites and T the number of primary periods, ordered by site-primary period. These covariates only used for dynamic (multi-season) models.

### Details

unmarkedFrameOccuTTD is the S4 class that holds data to be passed to the `occuTTD` model-fitting function.

### Value

an object of class unmarkedFrameOccuTTD

### Author(s)

Ken Kellner contact@kenkellner.com

### Examples

      # For a single-season model
      N <- 100 #Number of sites
      psi <- 0.4 #Occupancy probability
      lam <- 7 #Parameter for exponential distribution of time to detection
      Tmax <- 10 #Maximum survey length

      z <- rbinom(N, 1, psi) #Simulate occupancy
      y <- rexp(N, 1/lam) #Simulate time to detection
      y[z==0] <- Tmax
      y[y>Tmax] <- Tmax

      sc <- as.data.frame(matrix(rnorm(N*2),ncol=2)) #Site covs
      oc <- as.data.frame(matrix(rnorm(N*2),ncol=2)) #obs covs

      umf <- unmarkedFrameOccuTTD(y=y, surveyLength=Tmax, siteCovs=sc, obsCovs=oc)

[Package unmarked version 1.0.0 Index]