Fits one or more distributions to species sensitivity data.

ssd_fit_dists(
  data,
  left = "Conc",
  right = left,
  weight = NULL,
  dists = ssd_dists_bcanz(),
  nrow = 6L,
  rescale = FALSE,
  reweight = FALSE,
  computable = TRUE,
  at_boundary_ok = FALSE,
  min_pmix = 0,
  range_shape1 = c(0.05, 20),
  range_shape2 = range_shape1,
  control = list(),
  silent = FALSE
)

Arguments

Value

An object of class fitdists.

Details

By default the 'llogis', 'gamma' and 'lnorm' distributions are fitted to the data. For a complete list of the implemented distributions see ssd_dists_all().

If weight specifies a column in the data frame with positive numbers, weighted estimation occurs. However, currently only the resultant parameter estimates are available.

If the right argument is different to the left argument then the data are considered to be censored.

See also

Examples

fits <- ssd_fit_dists(ssddata::ccme_boron)
fits
#> Distribution 'gamma'
#>   scale 25.1268
#>   shape 0.950179
#> 
#> Distribution 'lgumbel'
#>   locationlog 1.92263
#>   scalelog 1.23224
#> 
#> Distribution 'llogis'
#>   locationlog 2.62628
#>   scalelog 0.740426
#> 
#> Distribution 'lnorm'
#>   meanlog 2.56164
#>   sdlog 1.24154
#> 
#> Distribution 'lnorm_lnorm'
#>   meanlog1 0.949539
#>   meanlog2 3.20109
#>   pmix 0.283985
#>   sdlog1 0.554545
#>   sdlog2 0.768816
#> 
#> Distribution 'weibull'
#>   scale 23.514
#>   shape 0.9661
#> 
#> Parameters estimated from 28 rows of data.
ssd_plot_cdf(fits)

ssd_hc(fits)
#> # A tibble: 1 × 10
#>   dist    percent   est    se   lcl   ucl    wt method     nboot pboot
#>   <chr>     <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <chr>      <int> <dbl>
#> 1 average       5  1.24    NA    NA    NA     1 parametric     0    NA