# Birds Dataset - Subset of the North American Breeding Bird Survey Dataset #' This dataset is a subset of the North American Breeding Bird Survey, containing data collected at 15 routes in Michigan, USA. Each route has 10 stops, and the dataset includes counts for 10 bird species. data ## Format A data frame with 600 rows and 13 columns: - **Route**: An identifier for the 15 survey sites. - **Year**: The year of the survey (numeric). - **English_Common_Name**: The English common name of the bird species surveyed (character). - **Stop1**: Count for replicate 1 at the site (numeric). - **Stop2**: Count for replicate 2 at the site (numeric). - **Stop3**: Count for replicate 3 at the site (numeric). - **Stop4**: Count for replicate 4 at the site (numeric). - **Stop5**: Count for replicate 5 at the site (numeric). - **Stop6**: Count for replicate 6 at the site (numeric). - **Stop7**: Count for replicate 7 at the site (numeric). - **Stop8**: Count for replicate 8 at the site (numeric). - **Stop9**: Count for replicate 9 at the site (numeric). - **Stop10**: Count for replicate 10 at the site (numeric). ## Source North American Breeding Bird Survey ([https://www.pwrc.usgs.gov/BBS/](https://www.pwrc.usgs.gov/BBS/)) ```r birds ``` ## Examples ```r # MNM Model #' # Example: Hurdle Model # Data must first be reformatted to an array of dimension (R,T,S,K) R <- 15 T <- 10 S <- 10 K <- 4 # Ensure data is ordered consistently birds <- birds[order(birds$Route, birds$Year, birds$English_Common_Name), ] # Create a 4D array with proper dimension Y <- array(NA, dim = c(R, T, S, K)) # Map route, species, and year to indices route_idx <- as.numeric(factor(birds$Route)) species_idx <- as.numeric(factor(birds$English_Common_Name)) year_idx <- as.numeric(factor(birds$Year)) # Populate the array stop_data <- as.matrix(birds[, grep("^Stop", colnames(birds))]) for (i in seq_len(nrow(birds))) { Y[route_idx[i], , species_idx[i], year_idx[i]] <- stop_data[i, ] } # Assign dimnames dimnames(Y) <- list( Route = sort(unique(birds$Route)), Stop = paste0("Stop", 1:T), Species = sort(unique(birds$English_Common_Name)), Year = sort(unique(birds$Year)) ) # Selecting only 5 bird species and 1 year for analysis: Y<-Y[,,1:5,1] model<-MNM_fit(Y=Y, AR=FALSE, Hurdle=FALSE) ```

birds dataset