View source: R/control.rds.estimates.R
| control.rds.estimates | R Documentation |
Auxiliary function as user interface for fine-tuning RDS.bootstrap.intervals algorithm, which computes interval estimates for via bootstrapping.
control.rds.estimates(
confidence.level = 0.95,
SS.infinity = 0.01,
discrete.cutoff = 0.8,
useC = TRUE,
number.of.bootstrap.samples = NULL,
hcg.reltol = sqrt(.Machine$double.eps),
hcg.BS.reltol = 1e+05 * sqrt(.Machine$double.eps),
hcg.max.optim = 500,
seed = NULL
)
confidence.level |
The confidence level for the confidence intervals. The default is 0.95 for 95%. |
SS.infinity |
The sample proportion, |
discrete.cutoff |
The minimum proportion of the values of the outcome variable that need to be unique before the variable is judged to be continuous. |
useC |
Use a C-level implementation of Gile's bootstrap (rather than the R level). The implementations should be computational equivalent (except for speed). |
number.of.bootstrap.samples |
The number of bootstrap samples to take
in estimating the uncertainty of the estimator. If |
hcg.reltol |
Relative convergence tolerance for the HCG estimator. The algorithm stops if
it is unable to reduce the log-likelihood by a factor of |
hcg.BS.reltol |
Relative convergence tolerance for the bootstrap of the HCG estimator.
It has the same interpretation as |
hcg.max.optim |
The number of iterations on the likelihood optimization for the HCG estimator. |
seed |
Seed value (integer) for the random number generator. See
|
This function is only used within a call to the RDS.bootstrap.intervals
function.
Some of the arguments are not yet fully implemented. It will evolve slower to incorporate more arguments as the package develops.
A list with arguments as components.
RDS.bootstrap.intervals,
RDS.bootstrap.mechanics
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