Display error distributions of given class.
error_distributions(err_dist = NULL, err_class = NULL)Vector of error distribution(s).
String that indicates the which error distributions to list.
0/1 data; ("bernoulli").
Binomial data represented as counts or proportions; ("binomial.count", "binomial.prop").
[0-1] data; ("tab", "zitab").
Count data; ("poisson", "negbin", "zip", "zinb", "zipl", "zinbl", "zipl.mu", "zinbl.mu").
Non-negative continous data; ("gaussian", "tweedie", "zig", "zigl", "zigl.mu", "ziig", "ziigl", "ziigl.mu").
If no arguments supplied, return a data frame listing all possible error distributions with corresponding error classes; if a vector of error classes is supplied, return corresponding error distributions; if a vector of error distributions is supplied, return corresponding error classes.
## Print data frame of all error distributions with corresponding error classes
error_distributions()
#> err_dist err_class
#> 1 bernoulli binary
#> 2 binomial.count binomial
#> 3 binomial.prop binomial
#> 4 poisson count
#> 5 negbin count
#> 6 zip count
#> 7 zinb count
#> 8 zipl count
#> 9 zinbl count
#> 10 zipl.mu count
#> 11 zinbl.mu count
#> 12 gaussian abundance
#> 13 tweedie abundance
#> 14 zig abundance
#> 15 zigl abundance
#> 16 zigl.mu abundance
#> 17 ziig abundance
#> 18 ziigl abundance
#> 19 ziigl.mu abundance
#> 20 tab percentage
#> 21 zitab percentage
## Print all error distributions
error_distributions(err_class="all")
#> [1] "bernoulli" "binomial.count" "binomial.prop" "poisson"
#> [5] "negbin" "zip" "zinb" "zipl"
#> [9] "zinbl" "zipl.mu" "zinbl.mu" "gaussian"
#> [13] "tweedie" "zig" "zigl" "zigl.mu"
#> [17] "ziig" "ziigl" "ziigl.mu" "tab"
#> [21] "zitab"
## Print error distributions for count data
error_distributions(err_class="count")
#> [1] "poisson" "negbin" "zip" "zinb" "zipl" "zinbl" "zipl.mu"
#> [8] "zinbl.mu"
## Print error classes for poisson and gaussian data
error_distributions(err_dist=c("poisson", "gaussian"))
#> [1] "count" "abundance"