params {ssdtools} | R Documentation |
Parameter Descriptions for ssdtools Functions
Description
Parameter Descriptions for ssdtools Functions
Arguments
... |
Unused. |
add_x |
The value to add to the label x values (before multiplying by |
all |
A flag specifying whether to also return transformed parameters. |
all_dists |
A flag specifying whether all the named distributions must fit successfully. |
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). |
average |
A flag specifying whether to provide model averaged values as opposed to a value for each distribution. |
bcanz |
A flag or NULL specifying whether to only include distributions in the set that is approved by BC, Canada, Australia and New Zealand for official guidelines. |
big.mark |
A string specifying used between every 3 digits to separate thousands on the x-axis. |
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. |
chk |
A flag specifying whether to check the arguments. |
ci |
A flag specifying whether to estimate confidence intervals (by bootstrapping). |
censoring |
A numeric vector of the left and right censoring values. |
color |
A string of the column in data for the color aesthetic. |
computable |
A flag specifying whether to only return fits with numerically computable standard errors. |
conc |
A numeric vector of concentrations to calculate the hazard proportions for. |
control |
A list of control parameters passed to |
data |
A data frame. |
delta |
A non-negative number specifying the maximum absolute AIC difference cutoff. Distributions with an absolute AIC difference greater than delta are excluded from the calculations. |
digits |
A whole number specifying the number of significant figures. |
dists |
A character vector of the distribution names. |
fitdists |
An object of class fitdists. |
hc |
A value between 0 and 1 indicating the proportion hazard concentration (or NULL). |
hc_value |
A number of the hazard concentration value to offset. |
label |
A string of the column in data with the labels. |
label_size |
A number for the size of the labels. |
left |
A string of the column in data with the concentrations. |
level |
A number between 0 and 1 of the confidence level of the interval. |
linecolor |
A string of the column in pred to use for the line color. |
linetype |
A string of the column in pred to use for the linetype. |
llocation |
location parameter on the log scale. |
location |
location parameter. |
locationlog |
location on the log scale parameter. |
locationlog1 |
locationlog1 parameter. |
locationlog2 |
locationlog2 parameter. |
log |
logical; if TRUE, probabilities p are given as log(p). |
log.p |
logical; if TRUE, probabilities p are given as log(p). |
lscale |
scale parameter on the log scale. |
lshape |
shape parameter on the log scale. |
lshape1 |
shape1 parameter on the log scale. |
lshape2 |
shape2 parameter on the log scale. |
lower.tail |
logical; if TRUE (default), probabilities are |
meanlog |
mean on log scale parameter. |
meanlog1 |
mean on log scale parameter. |
meanlog2 |
mean on log scale parameter. |
min_pboot |
A number between 0 and 1 of the minimum proportion of bootstrap samples that must successfully fit (return a likelihood) to report the confidence intervals. |
min_pmix |
A number between 0 and 0.5 specifying the minimum proportion in mixture models. |
npars |
A whole numeric vector specifying which distributions to include based on the number of parameters. |
all_estimates |
A flag specifying whether to calculate estimates for all implemented distributions. |
ci_method |
A string specifying which method to use for estimating the bootstrap values. Possible values are "multi_free" and "multi_fixed" which treat the distributions as constituting a single distribution but differ in whether the model weights are fixed and "weighted_samples" and "weighted_arithmetic" take bootstrap samples from each distribution proportional to its weight versus calculating the weighted arithmetic means of the lower and upper confidence limits. |
multi_est |
A flag specifying whether to treat the distributions as constituting a single distribution (as opposed to taking the mean) when calculating model averaged estimates. |
na.rm |
A flag specifying whether to silently remove missing values or remove them with a warning. |
n |
positive number of observations. |
nboot |
A count of the number of bootstrap samples to use to estimate the confidence limits. A value of 10,000 is recommended for official guidelines. |
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. |
object |
The object. |
parametric |
A flag specifying whether to perform parametric bootstrapping as opposed to non-parametrically resampling the original data with replacement. |
p |
vector of probabilities. |
percent |
A numeric vector of percent values to estimate hazard concentrations for. Deprecated for |
pmix |
Proportion mixture parameter. |
proportion |
A numeric vector of proportion values to estimate hazard concentrations for. |
pvalue |
A flag specifying whether to return p-values or the statistics (default) for the various tests. |
pred |
A data frame of the predictions. |
q |
vector of quantiles. |
range_shape1 |
A numeric vector of length two of the lower and upper bounds for the shape1 parameter. |
range_shape2 |
shape2 parameter. |
reweight |
A flag specifying whether to reweight weights by dividing by the largest weight. |
rescale |
A flag specifying whether to rescale concentration values by dividing by the geometric mean of the minimum and maximum positive finite values. |
ribbon |
A flag indicating whether to plot the confidence interval as a grey ribbon as opposed to green solid lines. |
right |
A string of the column in data with the right concentration values. |
save_to |
NULL or a string specifying a directory to save where the bootstrap datasets and parameter estimates (when successfully converged) to. |
samples |
A flag specfying whether to include a numeric vector of the bootstrap samples as a list column in the output. |
scale |
scale parameter. |
scalelog1 |
scalelog1 parameter. |
scalelog2 |
scalelog2 parameter. |
scalelog |
scale 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. |
select |
A character vector of the distributions to select. |
shape |
shape parameter. |
shape1 |
shape1 parameter. |
shape2 |
shape2 parameter. |
shift_x |
The value to multiply the label x values by (after adding |
silent |
A flag indicating whether fits should fail silently. |
size |
A number for the size of the labels. Deprecated for |
suffix |
Additional text to display after the number on the y-axis. |
tails |
A flag or NULL specifying whether to only include distributions with both tails. |
text_size |
A number for the text size. |
theme_classic |
A flag specifying whether to use the classic theme or the default. |
trans |
A string of which transformation to use. Accepted values include |
valid |
A flag or NULL specifying whether to include distributions with valid likelihoods that allows them to be fit with other distributions for modeling averaging. |
weight |
A string of the numeric column in data with positive weights less than or equal to 1,000 or NULL. |
x |
The object. |
xbreaks |
The x-axis breaks as one of:
|
xlimits |
The x-axis limits as one of:
|
xintercept |
The x-value for the intersect. |
xlab |
A string of the x-axis label. |
yintercept |
The y-value for the intersect. |
ylab |
A string of the x-axis label. |
burrIII3.weight |
weight parameter for the Burr III distribution. |
burrIII3.shape1 |
shape1 parameter for the Burr III distribution. |
burrIII3.shape2 |
shape2 parameter for the Burr III distribution. |
burrIII3.scale |
scale parameter for the Burr III distribution. |
gamma.weight |
weight parameter for the gamma distribution. |
gamma.shape |
shape parameter for the gamma distribution. |
gamma.scale |
scale parameter for the gamma distribution. |
gompertz.weight |
weight parameter for the Gompertz distribution. |
gompertz.location |
location parameter for the Gompertz distribution. |
gompertz.shape |
shape parameter for the Gompertz distribution. |
invpareto.weight |
weight parameter for the inverse Pareto distribution. |
invpareto.shape |
shape parameter for the inverse Pareto distribution. |
invpareto.scale |
scale parameter for the inverse Pareto distribution. |
lgumbel.weight |
weight parameter for the log-Gumbel distribution. |
lgumbel.locationlog |
location parameter for the log-Gumbel distribution. |
lgumbel.scalelog |
scale parameter for the log-Gumbel distribution. |
llogis.weight |
weight parameter for the log-logistic distribution. |
llogis.locationlog |
location parameter for the log-logistic distribution. |
llogis.scalelog |
scale parameter for the log-logistic distribution. |
llogis_llogis.weight |
weight parameter for the log-logistic log-logistic mixture distribution. |
llogis_llogis.locationlog1 |
locationlog1 parameter for the log-logistic log-logistic mixture distribution. |
llogis_llogis.scalelog1 |
scalelog1 parameter for the log-logistic log-logistic mixture distribution. |
llogis_llogis.locationlog2 |
locationlog2 parameter for the log-logistic log-logistic mixture distribution. |
llogis_llogis.scalelog2 |
scalelog2 parameter for the log-logistic log-logistic mixture distribution. |
llogis_llogis.pmix |
pmix parameter for the log-logistic log-logistic mixture distribution. |
lnorm.weight |
weight parameter for the log-normal distribution. |
lnorm.meanlog |
meanlog parameter for the log-normal distribution. |
lnorm.sdlog |
sdlog parameter for the log-normal distribution. |
lnorm_lnorm.weight |
weight parameter for the log-normal log-normal mixture distribution. |
lnorm_lnorm.meanlog1 |
meanlog1 parameter for the log-normal log-normal mixture distribution. |
lnorm_lnorm.sdlog1 |
sdlog1 parameter for the log-normal log-normal mixture distribution. |
lnorm_lnorm.meanlog2 |
meanlog2 parameter for the log-normal log-normal mixture distribution. |
lnorm_lnorm.sdlog2 |
sdlog2 parameter for the log-normal log-normal mixture distribution. |
lnorm_lnorm.pmix |
pmix parameter for the log-normal log-normal mixture distribution. |
weibull.weight |
weight parameter for the Weibull distribution. |
weibull.shape |
shape parameter for the Weibull distribution. |
weibull.scale |
scale parameter for the Weibull distribution. |