All the data sets are available, except faithful and tree which are
already in R.

Additional datasets to work our examples are:

VA, heart

The following are fully operational:

ginv		generalized inverse
write.matrix	write matrix or numeric data frame
eqscplot	equally-scaled plots
area		simple integration 
mvrnorm 	simulate from a multivariate normal distribution
truehist	histogram plots
nclass.scott	choose number of histogram classes
nclass.FD	choose number of histogram classes
hist.scott	histogram with other bin choices
hist.FD 	histogram with other bin choices
frequency.polygon
nclass.freq	choose number of classes for frequency polygon
kde2d		2D kernel density estimation
ucv, bcv	cross-validation functions for density
width.SJ	bandwidth choice for density.
contr.sdif	contrasts function for successive differences
stdres		standardized residuals for linear models
studres 	Studentized residuals for linear models
vcov		variance-covariance summary for linear, glm and 
		   non-linear regression fits
boxcox		estimate Box-Cox transformation
logtrans	estimate shift in log-transformations
fraction	methods for operating on rational fractions
stepAIC 	stepwise AIC minimization
addterm, dropterm  enhanced versions of add1 and drop1
dose.p		function for LD50-like fits
neg.bin 	negative binomial family with fixed theta
anova.negbin	functions for full negative binomial family
glm.convert
glm.nb
negative.binomial
rnegbin
theta.md
theta.mm
loglm		Object-oriented wrapper for loglin() (from complements)
gamma.shape	MLE of shape parameter for GLM fit with gamma family
gamma.dispersion		(from complements)
huber		Huber location with MAD scale
hubers		Huber proposal 2
rlm		robust linear model fitting (by Huber M-estimator)
deviance.nls	deviance function for nls fits
plot.profile	plot method for profiles
pairs.profile	pairs method for profiles
profile.glm	profiles for glm objects
lda		linear discrimination
predict.lda	predict function for lda
qda		quadratic discrimination
predict.qda	predict function for qda
sammon		Sammon non-linear mapping
isoMDS		isotonic multidimensional scaling
Shepard 	Shepard plot for isoMDS
corresp 	correspondence analysis
mca		multiple correspondence analysis (complements)
cpgram		cumulative periodogram
digamma, trigamma	first and second derivatives of log Gamma
		(even of complex argument).


The following depend on facilities not in R and so do not work:

Choleski	Choleski decompositions for Matrices
histplot	Trellis histogram plots
rms.curv	curvature measures for non-linear regression
deriv3		symbolic differentiation
D, make.call	extended functions
vcov.nlregb	vcov methods for nlregb objects
vcov.nlminb	vcov methods for nlminb objects


BDR <ripley@stats.ox.ac.uk> 1999/08/06

