EnvStats: ciNparN – R documentation

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ciNparN

Sample Size for Nonparametric Confidence Interval for a Quantile

Description

Compute the sample size necessary to achieve a specified confidence level for a nonparametric confidence interval for a quantile.

Usage

ciNparN(p = 0.5, lcl.rank = ifelse(ci.type == "upper", 0, 1), 
    n.plus.one.minus.ucl.rank = ifelse(ci.type == "lower", 0, 1), 
    ci.type = "two.sided", conf.level = 0.95)

Arguments

`p`	numeric vector of probabilities specifying the quantiles. All values of `p` must be between 0 and 1. The default value is `p=0.5`.
`lcl.rank, n.plus.one.minus.ucl.rank`	numeric vectors of non-negative integers indicating the ranks of the order statistics that are used for the lower and upper bounds of the confidence interval for the specified quantile(s). When `lcl.rank=1` that means use the smallest value as the lower bound, when `lcl.rank=2` that means use the second to smallest value as the lower bound, etc. When `n.plus.one.minus.ucl.rank=1` that means use the largest value as the upper bound, when `n.plus.one.minus.ucl.rank=2` that means use the second to largest value as the upper bound, etc. A value of `0` for `lcl.rank` indicates no lower bound (i.e., -Inf) and a value of `0` for `n.plus.one.minus.ucl.rank` indicates no upper bound (i.e., `Inf`). When `ci.type="upper"` then `lcl.rank` is set to `0` by default, otherwise it is set to `1` by default. When `ci.type="lower"` then `n.plus.one.minus.ucl.rank` is set to `0` by default, otherwise it is set to `1` by default.
`ci.type`	character string indicating what kind of confidence interval to compute. The possible values are `"two-sided"` (the default), `"lower"`, and `"upper"`.
`conf.level`	numeric vector of numbers between 0 and 1 indicating the confidence level associated with the confidence interval(s). The default value is `conf=0.95`.

Details

If the arguments p, lcl.rank, n.plus.one.minus.ucl.rank and conf.level are not all the same length, they are replicated to be the same length as the length of the longest argument.

The help file for eqnpar explains how nonparametric confidence intervals for quantiles are constructed and how the confidence level associated with the confidence interval is computed based on specified values for the sample size and the ranks of the order statistics used for the bounds of the confidence interval.

The function ciNparN determines the required the sample size via a nonlinear optimization.

Value

numeric vector of sample sizes.

Note

See the help file for eqnpar.

Author(s)

Steven P. Millard (EnvStats@ProbStatInfo.com)

References

See the help file for eqnpar.

Examples

# Look at how the required sample size for a confidence interval 
  # increases with increasing confidence level for a fixed quantile:

  seq(0.5, 0.9, by = 0.1) 
  #[1] 0.5 0.6 0.7 0.8 0.9 

  ciNparN(p = 0.9, conf.level=seq(0.5, 0.9, by = 0.1)) 
  #[1]  7  9 12 16 22

  #----------

  # Look at how the required sample size for a confidence interval increases 
  # as the quantile moves away from 0.5:

  ciNparN(p = seq(0.5, 0.9, by = 0.1)) 
  #[1]  6  7  9 14 29

EnvStats

Package for Environmental Statistics, Including US EPA Guidance

v2.4.0

GPL (>= 3)

Authors

Steven P. Millard [aut], Alexander Kowarik [ctb, cre] (<https://orcid.org/0000-0001-8598-4130>)

Initial release

2020-10-20