# Create an unmarkedFrameOccuTTD object for the time-to-detection model fit by occuTTD Organizes time-to-detection occupancy data along with covariates. This S4 class is required by the data argument of `occuTTD` ```r unmarkedFrameOccuTTD(y, surveyLength, siteCovs=NULL, obsCovs=NULL, numPrimary=1, yearlySiteCovs=NULL) ``` ## Arguments - `y`: An MxR matrix of time-to-detection 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. ## Note If the time-to-detection values in `y` are very large (e.g., because they are expressed as numbers of seconds) you may have issues fitting models. An easy solution is to convert your units (e.g., from seconds to decimal minutes) to keep the values as close to 0 as possible. ## Returns an object of class unmarkedFrameOccuTTD ## Author(s) Ken Kellner contact@kenkellner.com ## Examples ```r # 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) ```

unmarkedFrameOccuTTD function