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
)
An object of class fitdists.
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.
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