Fit SSD Distributions to Simulated Data
Usage
ssd_fit_dists_sims(
x,
dists = ssdtools::ssd_dists_bcanz(),
...,
rescale = FALSE,
computable = FALSE,
at_boundary_ok = TRUE,
min_pmix = list(ssdtools::ssd_min_pmix),
range_shape1 = list(c(0.05, 20)),
range_shape2 = range_shape1,
seed = NULL,
silent = TRUE,
.progress = FALSE
)Arguments
- x
A data frame with sim and stream integer columns and a list column of the data frames to fit distributions to.
- dists
A character vector of the distribution names.
- ...
Additional arguments passed to
ssdtools::ssd_fit_dists().- rescale
A flag specifying whether to leave the values unchanged (FALSE) or to rescale concentration values by dividing by the geometric mean of the minimum and maximum positive finite values (TRUE) or a string specifying whether to leave the values unchanged ("no") or to rescale concentration values by dividing by the geometric mean of the minimum and maximum positive finite values ("geomean") or to logistically transform ("odds").
- computable
A flag specifying whether to only return fits with numerically computable standard errors.
- at_boundary_ok
A flag specifying whether a model with one or more parameters at the boundary should be considered to have converged (default = TRUE).
- min_pmix
A list of one or more functions with a single argument that inputs the number of rows of data and returns a proportion between 0 and 0.5.
- range_shape1
A list of numeric vectors of length two of the lower and upper bounds for the shape1 parameter.
- range_shape2
A list of numeric vectors of length two of the lower and upper bounds for the shape2 parameter.
- seed
An integer of the starting seed or NULL.
- silent
A flag indicating whether fits should fail silently.
- .progress
Whether to show a
purrr::progress bar.