RDS: control.rds.estimates – R documentation

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control.rds.estimates

Auxiliary for Controlling RDS.bootstrap.intervals

Description

Auxiliary function as user interface for fine-tuning RDS.bootstrap.intervals algorithm, which computes interval estimates for via bootstrapping.

Usage

control.rds.estimates(
  confidence.level = 0.95,
  SS.infinity = 0.01,
  lowprevalence = c(8, 14),
  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
)

Arguments

`confidence.level`	The confidence level for the confidence intervals. The default is 0.95 for 95%.
`SS.infinity`	The sample proportion, `n/N`, below which the computation of the SS weights should simplify to that of the `RDS-II` weights.
`lowprevalence`	Standard confidence interval procedures can be inaccurate when the outcome expected count is close to zero. This sets conditions where alternatives to the standard are used for the `ci.type="hmg"` option. See Details for its use.
`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 `NULL` it defaults to the number necessary to compute the standard error to accuracy 0.001.
`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 `reltol * (abs(log-likelihood) + reltol)` at a step. Defaults to `sqrt(.Machine$double.eps)`, typically about `1e-8`.
`hcg.BS.reltol`	Relative convergence tolerance for the bootstrap of the HCG estimator. It has the same interpretation as `hcg.reltol` except it is applied to each bootstrap sample. It is typically the same or larger than `hcg.reltol`.
`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 `set.seed`

Details

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.

Standard confidence interval procedures can be inaccurate when the outcome expected count is close to zero. In these cases the combined Agresti-Coull and the bootstrap-t interval of Mantalos and Zografos (2008) can be used. The lowprevalence argument is a two vector parameter setting the conditions under which the approximation is used. The first is the penalty term on the differential activity. If the observed number of the rare group minus the product of the first parameter and the differential activity is lower than the second parameter, the low prevalence approximation is used.

Value

A list with arguments as components.