normCI: Confidence Intervals for Mean and Standard Deviation

In MKinfer: Inferential Statistics

Confidence Intervals for Mean and Standard Deviation

Description

This function can be used to compute confidence intervals for mean and standard deviation of a normal distribution.

Usage

normCI(x, mean = NULL, sd = NULL, conf.level = 0.95, 
       boot = FALSE, R = 9999, bootci.type = "all", na.rm = TRUE, 
       alternative = c("two.sided", "less", "greater"), ...)
meanCI(x, conf.level = 0.95, boot = FALSE, R = 9999, bootci.type = "all", 
       na.rm = TRUE, alternative = c("two.sided", "less", "greater"), ...)
sdCI(x, conf.level = 0.95, boot = FALSE, R = 9999, bootci.type = "all", 
     na.rm = TRUE, alternative = c("two.sided", "less", "greater"), ...)

Arguments

x	vector of observations.
mean	mean if known otherwise NULL.
sd	standard deviation if known otherwise NULL.
conf.level	confidence level.
boot	a logical value indicating whether bootstrapped confidence intervals shall be computed.
R	number of bootstrap replicates.
bootci.type	type of bootstrap interval; see boot.ci.
na.rm	a logical value indicating whether NA values should be stripped before the computation proceeds.
alternative	a character string specifying one- or two-sided confidence intervals. Must be one of "two.sided" (default), "greater" or "less" (one-sided intervals). You can specify just the initial letter.
...	further arguments passed to function boot, e.g. for parallel computing.

Details

The standard confidence intervals for mean and standard deviation are computed that can be found in many textbooks, e.g. Chapter 4 in Altman et al. (2000).

In addition, bootstrap confidence intervals for mean and/or SD can be computed, where function boot.ci is applied.

Value

A list with class "confint" containing the following components:

estimate	the estimated mean and sd.
conf.int	confidence interval(s) for mean and/or sd.
Infos	additional information.

Author(s)

Matthias Kohl [e-mail]

References

D. Altman, D. Machin, T. Bryant, M. Gardner (eds). Statistics with Confidence: Confidence Intervals and Statistical Guidelines, 2nd edition 2000.

Examples

x <- rnorm(50)
## mean and sd unknown
normCI(x)
meanCI(x)
sdCI(x)

## one-sided
normCI(x, alternative = "less")
meanCI(x, alternative = "greater")
sdCI(x, alternative = "greater")

## bootstrap intervals (R = 999 to reduce computation time for R checks)
normCI(x, boot = TRUE, R = 999)
meanCI(x, boot = TRUE, R = 999)
sdCI(x, boot = TRUE, R = 999)

normCI(x, boot = TRUE, R = 999, alternative = "less")
meanCI(x, boot = TRUE, R = 999, alternative = "less")
sdCI(x, boot = TRUE, R = 999, alternative = "greater")

## sd known
normCI(x, sd = 1)
## bootstrap intervals only for mean (sd is ignored)
## (R = 999 to reduce computation time for R checks)
normCI(x, sd = 1, boot = TRUE, R = 999)

## mean known
normCI(x, mean = 0)
## bootstrap intervals only for sd (mean is ignored)
## (R = 999 to reduce computation time for R checks)
normCI(x, mean = 0, boot = TRUE, R = 999)


## parallel computing for bootstrap
normCI(x, boot = TRUE, R = 9999, parallel = "multicore", ncpus = 2)

MKinfer documentation built on April 17, 2023, 9:10 a.m.