- The R Statistical Computer Language
- Some R scripts. For a file
foo.R
the following command run outside R from the operating system command lineR CMD BATCH --vanilla foo.R
produces a file
foo.Rout
that has all the results (whatever R would print if every command in the file were typed in to R).- binom.R and binom.Rout statistical inference for binomial distributions (section 1.4 in Agresti). This file has been redone in R markdown to serve as an R markdown example too. That is found in the Course Notes section of this web site.
- coverage.R and coverage.Rout and coverage.pdf coverage of confidence interval for binomial distributions.
- The former
multi-simple.R
andmulti-simple.Rout
have been moved to the Course Notes section. - The former files
-
multi.R
, -
likelihood.R
, -
likelihood-easier.R
, -
likelihood-factory.R
,
Rout
) files have been combined in a new handout on Likelihood Computation found in the course notes section. -
- mcmc.R and mcmc.Rout and mcmc.pdf Bayesian inference via Markov chain Monte Carlo (section 1.6 in Agresti)
- mcmc-too.R and mcmc-too.Rout and mcmc-too.pdf more Bayesian inference via Markov chain Monte Carlo (section 1.6 in Agresti)
- expfam-samp.R and expfam-samp.Rout some examples that go with exponential families, now obsolete, see the handout on exponential families, which has many more examples.
- step.R
and step.Rout using the R function
step
- s3-try3.R
and s3-try3.Rout using the R function
glmbb
in the CRAN packageglmbb
that uses the branch and bound algorithm to find all models having criterion (AIC, BIC, or AICc) less than the minimum value of the criterion plus a specified cutoff. - a computer example from Stat 5102 about other link functions for Bernoulli regression (see also under course notes).
- polr.R
and polr.Rout using the R function
polr
in theMASS
package (which is arecommended
package that is always installed in R) which does POLR (proportional odds logistic regression) for ordered categorical response. - over.R
and over.Rout using the
quasipoisson
argument to the R functionglm
to do overdispersed Poisson. - graph.R
and graph.Rout using the
glmbb
function withgraphical = TRUE
.