MKinfer (version 0.5)

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"))

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.

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.

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

# NOT RUN {
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)
# }