66 lines
2.4 KiB
Text
66 lines
2.4 KiB
Text
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\name{bootstrap.mean.test}
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\alias{bootstrap.mean.test}
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\title{Bootstrap Test for Means}
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\description{Performs one and two sample bootstrap tests for means on vectors of data}
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\usage{
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bootstrap.mean.test(x, ...)
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## Default method:
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bootstrap.mean.test(x, y = NULL, alternative = c("two.sided", "less", "greater"), mu = 0, conf.level = 0.95, bootstrap_samples = 1e+06)
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}
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\arguments{
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\item{x}{a (non-empty) numeric vector of data values.}
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\item{y}{an optional (non-empty) numeric vector of data values.}
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\item{alternative}{a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "greater" or "less". You can specify just the initial letter.}
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\item{mu}{a number indicating the true value of the mean (or difference in means if you are performing a two sample test).}
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\item{conf.level}{confidence level of the interval.}
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\item{bootstrap_samples}{the number of bootstrap replicants to generate. Influences the accuracy of the p-value and confidence interval}
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}
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\details{
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alternative = "greater" is the alternative that x has a larger mean than y.
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If the input data are effectively constant (compared to the larger of the two means) an error is generated.
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}
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\value{
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A list with class \code{"htest"} containing the following components:
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\item{p.value}{the p-value for the test.}
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\item{conf.int}{a confidence interval for the mean appropriate to the
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specified alternative hypothesis.}
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\item{estimate}{the estimated mean or difference in means depending on
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whether it was a one-sample test or a two-sample test.}
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\item{null.value}{the specified hypothesized value of the mean or mean
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difference depending on whether it was a one-sample test or a
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two-sample test.}
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\item{alternative}{a character string describing the alternative
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hypothesis.}
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\item{method}{a character string indicating what type of t-test was
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performed.}
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\item{data.name}{a character string giving the name(s) of the data.}
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}
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\references{
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Gould, Rob. Bootstrap Hypothesis Test. PDF.
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http://www.stat.ucla.edu/~rgould/110as02/bshypothesis.pdf
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Myung, Jay. Bootstrap Hypothesis Testing. PDF.
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http://faculty.psy.ohio-state.edu/myung/personal/course/826/bootstrap_hypo.pdf
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}
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\author{
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Brandon Rozek (brozek@mail.umw.edu)
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}
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\seealso{
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\code{\link{t.test}}
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}
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\examples{
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x = rnorm(200, 2, 5)
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y = rnorm(200, 2, 5)
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# One sample test
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bootstrap.mean.test(x, mu = 1)
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# Two sample test
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bootstrap.mean.test(x, y)
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}
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\keyword{htest}
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