MKinfer (version 0.6)

normCI: 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"))

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.

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.

Author

Matthias Kohl

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.

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)