languageR-package {languageR}R Documentation

Data sets and functions for 'Analyzing Linguistic Data'

Description

Data sets and functions accompanying 'Analyzing Linguistic Data: A practical introduction to statistics', Cambridge University Press, 2007.

Details

Package: languageR
Type: Package
Version: 1.0
Date: 2007-01-15
License: GNU public license

The main function of this package is to make available the data sets discussed and analyzed in 'Analyzing Linguistic Data: A practical introduction to statistics'. The following packages should be installed:

Design
for regression modeling
rpart
for CART trees
e1071
for support vector machines
lme4
for mixed-effects models
coda
for Markov-Chain Monte Carlo estimation
MASS
for many useful functions
zipfR
for word frequency distributions
ape
for phylogenetic clustering

The main convenience functions in this library are, by category:

correspondence analysis
(extending code by Murtagh)
corres.fnc
correspondence analysis
corsup.fnc
supplementary data
vocabulary richness
(supplementing current zipfR functionality)
compare.richness.fnc
for two texts, compare richness
growth.fnc
empirical vocabulary growth data for text
growth2vgc
conversion to vgc object of zipfR
spectrum.fnc
creates frequency spectrum
text2spc.fnc
conversion to spc object of zipfR
lmer functions
(p-values for mixed-effects models with lme4)
pvals.fnc
p-values for table of coefficients including MCMC
aovlmer.fnc
p-values for anova tables and/or MCMC p-value for specified factor
simulation functions
(for comparing mixed models with traditional techniques including F1, F2, and F1+F2)
simulateRegression.fnc
simulate simple regression design
simulateSplitPlot.fnc
simulate simple split-plot design
simulateLatinsquare.fnc
simulating simple Latin-square design
miscellaneous
(convenience functions)
pairscor.fnc
scatterplot matrix with correlation tests
collin.fnc
collinearity diagnostics
pvals.fnc
p-values and MCMC confidence intervals for mixed models
plot.logistic.fit.fnc
diagnostic visualization for logistic models
xylowess.fnc
trellis scatterplots with smoother
mvrnormplot.fnc
scatterplot for bivariate standard normal random numbers with regression line

Author(s)

R. H. Baayen

Radboud University Nijmegen and Max Planck Institute for Psycholinguistics Nijmegen, The Netherlands

baayen@mpi.nl

Maintainer: baayen@mpi.nl

References

R. H. Baayen (2007) Analyzing Linguistic Data: A practical introduction to statistics, Cambridge: Cambridge University Press.

Examples

  library(languageR)
  data(package="languageR")

[Package languageR version 0.1 Index]