# Create an object of class unmarkedFrameMMO that contains data used by multmixOpen. Organizes count data and experimental design information from multiple primary periods along with associated covariates. This S4 class is required by the data argument of `multmixOpen` ```r unmarkedFrameMMO(y, siteCovs=NULL, obsCovs=NULL, yearlySiteCovs=NULL, numPrimary, type, primaryPeriod) ``` ## Arguments - `y`: An MxJT matrix of the repeated count data, where M is the number of sites (i.e., points or transects), J is the number of distance classes and T is the maximum number of primary sampling periods per site - `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 MxJT rows in site-major order. - `yearlySiteCovs`: Either a named list of MxT `data.frame`s, or a site-major `data.frame` with MT rows and 1 column per covariate - `numPrimary`: Maximum number of observed primary periods for each site - `type`: Either "removal" for removal sampling, "double" for standard double observer sampling, or "depDouble" for dependent double observer sampling - `primaryPeriod`: An MxJT matrix of integers indicating the primary period of each observation ## Details `unmarkedFrameMMO` is the S4 class that holds data to be passed to the `multmixOpen` model-fitting function. Options for the detection process (`type`) include equal-interval removal sampling (`"removal"`), double observer sampling (`"double"`), or dependent double-observer sampling (`"depDouble"`). Note that unlike the related functions `multinomPois` and `gmultmix`, custom functions for the detection process (i.e., `piFun`s) are not supported. To request additional options contact the author. When gamma or omega are modeled using year-specific covariates, the covariate data for the final year will be ignored; however, they must be supplied. If the time gap between primary periods is not constant, an M by T matrix of integers should be supplied using the `primaryPeriod` argument. ## Returns an object of class unmarkedFrameMMO ## See Also `unmarkedFrame-class`, `unmarkedFrame`, `multmixOpen` ## Examples ```r #Generate some data set.seed(123) lambda=4; gamma=0.5; omega=0.8; p=0.5 M <- 100; T <- 5 y <- array(NA, c(M, 3, T)) N <- matrix(NA, M, T) S <- G <- matrix(NA, M, T-1) for(i in 1:M) { N[i,1] <- rpois(1, lambda) y[i,1,1] <- rbinom(1, N[i,1], p) # Observe some Nleft1 <- N[i,1] - y[i,1,1] # Remove them y[i,2,1] <- rbinom(1, Nleft1, p) # ... Nleft2 <- Nleft1 - y[i,2,1] y[i,3,1] <- rbinom(1, Nleft2, p) for(t in 1:(T-1)) { S[i,t] <- rbinom(1, N[i,t], omega) G[i,t] <- rpois(1, gamma) N[i,t+1] <- S[i,t] + G[i,t] y[i,1,t+1] <- rbinom(1, N[i,t+1], p) # Observe some Nleft1 <- N[i,t+1] - y[i,1,t+1] # Remove them y[i,2,t+1] <- rbinom(1, Nleft1, p) # ... Nleft2 <- Nleft1 - y[i,2,t+1] y[i,3,t+1] <- rbinom(1, Nleft2, p) } } y=matrix(y, M) #Create some random covariate data sc <- data.frame(x1=rnorm(100)) #Create unmarked frame umf <- unmarkedFrameMMO(y=y, numPrimary=5, siteCovs=sc, type="removal") summary(umf) ```

unmarkedFrameMMO function