params: Parameter Descriptions for ssdtools Functions
In ssdtools: Species Sensitivity Distributions

params

R Documentation

Parameter Descriptions for ssdtools Functions

Description

Parameter Descriptions for ssdtools Functions

Arguments

`all`	A flag specifying whether to also return transformed parameters.
`at_boundary_ok`	A flag specifying whether a model with one or more parameters at the boundary should be considered to have converged (default = FALSE).
`x`	The object.
`object`	The object.
`control`	A list of control parameters passed to `stats::optim()`.
`chk`	A flag specifying whether to check the arguments.
`data`	A data frame.
`pred`	A data frame of the predictions.
`xlab`	A string of the x-axis label.
`ylab`	A string of the x-axis label.
`xbreaks`	The x-axis breaks as one of: `NULL` for no breaks `waiver()` for the default breaks A numeric vector of positions
`breaks`	A character vector
`bounds`	A named non-negative numeric vector of the left and right bounds for uncensored missing (0 and Inf) data in terms of the orders of magnitude relative to the extremes for non-missing values.
`conc`	A numeric vector of concentrations.
`digits`	A whole number specifying the number of significant figures
`percent`	A numeric vector of percentages.
`pvalue`	A flag specifying whether to return p-values or the statistics (default) for the various tests.
`parametric`	A flag specifying whether to perform parametric as opposed to non-parametric bootstrapping.
`min_pmix`	A number between 0 and 0.5 specifying the minimum proportion in mixture models.
`delta`	A non-negative number specifying the maximum absolute Akaike Information-theoretic Criterion difference cutoff. Distributions with an absolute difference from the best model greater than the cutoff are excluded.
`average`	A flag specifying whether to model average the estimates.
`ci`	A flag specifying whether to estimate confidence intervals (by parametric bootstrapping).
`nboot`	A count of the number of bootstrap samples to use to estimate the se and confidence limits. A value of 10000 is recommended for official guidelines.
`min_pboot`	A number of the minimum proportion of bootstrap samples that must successfully fit in the sense of returning a likelihood.
`level`	A number between 0 and 1 of the confidence level.
`...`	Unused.
`q`	vector of quantiles.
`p`	vector of probabilities.
`n`	number of observations.
`log`	logical; if TRUE, probabilities p are given as log(p).
`log.p`	logical; if TRUE, probabilities p are given as log(p).
`lower.tail`	logical; if TRUE (default), probabilities are `P[X <= x]`,otherwise, `P[X > x]`.
`location`	location parameter.
`llocation`	location parameter on the log scale.
`scale`	scale parameter.
`lscale`	scale parameter on the log scale.
`shape1`	shape1 parameter.
`shape2`	shape2 parameter.
`range_shape1`	A numeric vector of length two of the lower and upper bounds for the shape1 parameter.
`range_shape2`	shape2 parameter.
`locationlog1`	locationlog1 parameter.
`scalelog1`	scalelog1 parameter.
`locationlog2`	locationlog2 parameter.
`scalelog2`	scalelog2 parameter.
`pmix`	Proportion mixture parameter.
`meanlog`	mean on log scale parameter.
`meanlog1`	mean on log scale parameter.
`meanlog2`	mean on log scale parameter.
`locationlog`	location on log scale parameter.
`sdlog`	standard deviation on log scale parameter.
`sdlog1`	standard deviation on log scale parameter.
`sdlog2`	standard deviation on log scale parameter.
`scalelog`	scale on log scale parameter.
`lshape`	shape parameter on the log scale.
`lshape1`	shape1 parameter on the log scale.
`lshape2`	shape2 parameter on the log scale.
`xintercept`	The x-value for the intersect
`yintercept`	The y-value for the intersect.
`select`	A character vector of the distributions to select.
`rescale`	A flag specifying whether to rescale concentration values by dividing by the largest finite value.
`reweight`	A flag specifying whether to reweight weights by dividing by the largest weight.
`left`	A string of the column in data with the concentrations.
`right`	A string of the column in data with the right concentration values.
`label`	A string of the column in data with the labels.
`shape`	A string of the column in data for the shape aesthetic.
`color`	A string of the column in data for the color aesthetic.
`size`	A number for the size of the labels.
`ribbon`	A flag indicating whether to plot the confidence interval as a grey ribbon as opposed to green solid lines.
`shift_x`	The value to multiply the label x values by.
`hc`	A count between 1 and 99 indicating the percent hazard concentration (or NULL).
`weight`	A string of the numeric column in data with positive weights less than or equal to 1,000 or NULL.
`dists`	A character vector of the distribution names.
`computable`	A flag specifying whether to only return fits with numerically computable standard errors.
`silent`	A flag indicating whether fits should fail silently.
`na.rm`	A flag specifying whether to silently remove missing values or remove them with a warning.
`nrow`	A positive whole number of the minimum number of non-missing rows.
`nsim`	A positive whole number of the number of simulations to generate.
`linetype`	A string of the column in pred to use for the linetype.
`linecolor`	A string of the column in pred to use for the line color.