Analyzing Linguistic Data: A Practical Introduction to Statistics
Autocorrelation trellis graph
Compute p-values for factors in mixed models
Calculate condition number with intercept included
Compare Lexical Richness of Two Texts
Class "corres"
Correspondence Analysis
Initialize correspondence object
Supplementary rows or columns in correspondence analysis
Extract degree of polynomial or knots for restricted cubic spline
Extracts knots from variable name
calculate HPD prediction intervals
determine position for labels for interaction plots
Extracts range of predicted values from list of data frames
extract simple name of predictor from expression with poly
Class "growth"
Calculate vocabulary growth curve and vocabulary richness measures
Conversion of growth object into a vgc object
Initialize a vocabulary growth object.
Returns first rows of a growth object.
Herdan's C
implement interactions in the model matrix
Function for by-item regression used by simulateRegression.fnc
By-item anova for simulated data for quasi-F analysis
Calculate vector at specified lag
Data sets and functions for 'Analyzing Linguistic Data'
Plot the interaction of two linear numeric predictors in a model fitte...
Make a simulated data set with regression design
Create model matrix with main effects only
generate simulated data set with nonlinear function
Scatterplot of bivariate standard normal distribution
Scatterplot matrix with correlations
parse character string specifying restricted cubic spline
Plot method for correspondence objects
Plot method for growth objects
Plot for goodness of fit of logistic regression
create plot or plots for list with data frames for plot or subplots
plot a mer object
determine X and Y values for a given (sub)plot
Print method for correspondence object
Print method for growth objects.
Compute p-values and MCMC confidence intervals for mixed models
Quasi-F test
Quasi-F test for specific simple design
Shade rejection region for normal probability density function
Plot method for growth objects.
Simulate simple Latin Square data and compare models
Simulate data for quasi-F analysis and compare models
Simulate regression data and compare models
Frequency spectrum from text vector
By-subject analysis of simple Latin Square data sets
By-subject analysis of data sets requiring quasi-F ratios
Summarize a correspondence object
Summary method for growth objects
Show last rows of growth object.
Create a frequency spectrum from a text vector
transform vector according to specified function
Trellis scatterplot with smoothers
Yule's characteristic constant K
Zipf's rank frequency distribution
Data sets exemplifying statistical methods, and some facilitatory utility functions used in ``Analyzing Linguistic Data: A practical introduction to statistics using R'', Cambridge University Press, 2008.