Organize data for the multispecies occupancy model fit by occuMulti

Organizes detection, non-detection data for multiple species along with the covariates. This S4 class is required by the data argument of occuMulti

unmarkedFrameOccuMulti(y, siteCovs=NULL, obsCovs=NULL, 
                              maxOrder, mapInfo)

Arguments

y

A list (optionally a named list) of length S where each element is an MxJ matrix of the detection, non-detection data for one species, where M is the number of sites, J is the maximum number of sampling periods per site, and S is the number of species in the analysis.

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.frames of covariates that vary within sites, or a data.frame with MxJ rows in site-major order.

maxOrder

Optional; specify maximum interaction order. Defaults to number of species (all possible interactions). Reducing this value may speed up creation of unmarked frame if you aren't interested in higher-order interactions.

mapInfo

Currently ignored

Details

unmarkedFrameOccuMulti is the S4 class that holds data to be passed to the occuMulti model-fitting function.

Value

an object of class unmarkedFrameOccuMulti

Author

Ken Kellner contact@kenkellner.com

See also

unmarkedFrame-class, unmarkedFrame, occuMulti

Examples

# Fake data
S <- 3 # number of species
M <- 4 # number of sites
J <- 3 # number of visits

y <- list(matrix(rbinom(M*J,1,0.5),M,J), # species 1
          matrix(rbinom(M*J,1,0.5),M,J), # species 2
          matrix(rbinom(M*J,1,0.2),M,J)) # species 3

site.covs <- data.frame(x1=1:4, x2=factor(c('A','B','A','B')))
site.covs
#>   x1 x2
#> 1  1  A
#> 2  2  B
#> 3  3  A
#> 4  4  B

umf <- unmarkedFrameOccuMulti(y=y, siteCovs=site.covs, 
    obsCovs=NULL)   # organize data
umf                     # look at data
#> Data frame representation of unmarkedFrame object.
#> Only showing observation matrix for species 1.
#>   y.1 y.2 y.3 x1 x2
#> 1   0   1   1  1  A
#> 2   0   0   1  2  B
#> 3   0   0   1  3  A
#> 4   0   1   1  4  B
summary(umf)            # summarize      
#> unmarkedFrame Object
#> 
#> 4 sites
#> 3 species: sp1 sp2 sp3 
#> Maximum number of observations per site: 3 
#> Mean number of observations per site:
#> sp1: 3  sp2: 3  sp3: 3  
#> Sites with at least one detection:
#> sp1: 4  sp2: 4  sp3: 0  
#> Tabulation of y observations:
#> sp1:
#> 0 1 
#> 6 6 
#> sp2:
#> 0 1 
#> 7 5 
#> sp3:
#>  0 
#> 12 
#> 
#> Site-level covariates:
#>        x1       x2   
#>  Min.   :1.00   A:2  
#>  1st Qu.:1.75   B:2  
#>  Median :2.50        
#>  Mean   :2.50        
#>  3rd Qu.:3.25        
#>  Max.   :4.00        
plot(umf)               # visualize

#fm <- occu(~1 ~1, umf)  # fit a model