Learn R Programming

jmuOutlier (version 2.2)

jmuOutlier-package: Permutation Tests for Nonparametric Statistics

Description

Performs a permutation test on the difference between two location parameters, a permutation correlation test, a permutation F-test, the Siegel-Tukey test, a ratio mean deviance test. Also performs some graphing techniques, such as for confidence intervals, vector addition, and Fourier analysis; and includes functions related to the Laplace (double exponential) and triangular distributions. Performs power calculations for the binomial test.

Arguments

Details

(I) Permutation tests

  • perm.cor.test performs a permutation test based on Pearson and Spearman correlations.

  • perm.f.test performs a permutation F-test and a one-way analysis of variance F-test.

  • perm.test performs one-sample and two-sample permutation tests on vectors of data.

  • rmd.test performs a permutation test based on the estimated RMD, the ratio of the mean of the absolute value of the deviances, using two datasets.

  • siegel.test performs the Siegel-Tukey test using two datasets.

(II) Confidence intervals

  • CI.t.test produces two-sided confidence intervals on population mean, allowing for a finite population correction.

  • quantileCI produces exact confidence intervals on quantiles corresponding to the stated probabilities, based on the binomial test.

(III) Graphs

  • coin.toss illustrates the Law of Large Numbers for proportions.

  • fourier determines the Fourier approximation for any function on domain \((0, 2\pi)\) and then graphs both the function and the approximation.

  • lineGraph constructs a line graph on a vector of numerical observations.

  • plotCI plots multiple confidence intervals on the same graph, and determines the proportion of confidence intervals containing the true population mean.

  • plotEcdf graphs one or two empirical cumulative distribution functions on the same plot.

  • plotVector plots one or two 2-dimensional vectors along with their vector sum.

  • truncHist produces a truncated histogram, which may be useful if data contain some extreme outliers.

(IV) Laplace (double exponential) and symmetric triangular distributions

  • dlaplace, plaplace, qlaplace, and rlaplace give the density, the distribution function, the quantile function, and random deviates, respectively, of the Laplace distribution.

  • dtriang, ptriang, qtriang, and rtriang give the density, the distribution function, the quantile function, and random deviates, respectively, of the triangular distribution.

(V) Reading datasets

  • read.table2 reads table of data from author's website.

  • scan2 scans data from author's website.

(VI) Additional functions

  • abbreviation determines if one character variable is an abbreviation among a selection of other character variables.

  • latin generates a Latin square.

  • power.binom.test computes the power of the binomial test of a simple null hypothesis about a population median.

  • score generates van der Waerden scores (i.e., normal quantiles) and exponential (similar to Savage) scores.

References

Higgins, J. J. (2004) Introduction to Modern Nonparametric Statistics.

See Also

R-package coin for additional permutation tests, and R-package fastGraph.

Examples

Run this code
# NOT RUN {
print( x <- rtriang(20,50) ) 

perm.test( x, mu=25, stat=median )

quantileCI( x, c(0.25, 0.5, 0.75)  )

power.binom.test( 20, 0.05, "less", 47, plaplace, 45.2, 3.7 )

fourier (function(x){ (x-pi)^3 }, 4 )
# }

Run the code above in your browser using DataLab