Hebrew University of Jerusalem
Mt. Scopus, Jerusalem, ISRAEL
Explaining the Bootstrap
IBEE Computer Code
The following two files describe and contain the
S-plus code used to compute the IBEE
and Independence estimates for the Meron vegetation data in "Analyzing Spatially
Distributed Binary Data Using Independent-Block Estimating Equations" by Oman,
Landsman, Carmel and Kadmon.
The code may be used for binary responses from an equally-spaced rectangular grid,
and uses an exponential covariance function for the latent normal field (it may be
easily adapted to handle other types of covariance functions).
The S-plus statements are in a number of programs ( ibee.1 - ibee.6) which are to be
run sequentially. Before running them, the user must prepare data matrices and define
a number of parameters, as described in the comments of ibee.1. The programs use a
number of functions, whose code is also available.
ibee.readme.rtf Contains a brief description of the programs, the names of the functions,
and the calling sequence for the functions.
the code for ibee.1 - ibee.6 and the functions, as one long
The first line of each program or function is in boldface, and the last line
is followed by a blank line, in order to simplify copying and pasting into
the Splus window. The programs and functions have numerous
syllabus.rtf Course syllabus.
glim.formulas.pdf Some formulas (exponential family, derivatives of log-likelihood, ...).
medfly.doc Description of data set on medfly trappings.
medfly.data.txt Medfly data set.
medfly.data.tab.txt Medfly data set; tab-delimited and contains variable names.
meron.1.doc Description of data set on vegetation growth in Mt Meron.
meron.200.glim.txt Mt Meron data set.
exercise.0.soln.pdf Solution to exercise 0.
exercise.1.doc Exercise 1.
mvf.pdf Derivation of formulas for E(Y) and var(Y) in terms of the natural parameter .
medfly.explor.R R code for exploratory analysis of medfly data.
medfly.explor.doc Results of exploratory analysis.
exercise.1.soln.pdf Solution to Exercise 1.
medfly.poisson.2.R Code to fit a Poisson regression to the medfly data.
medfly.poisson.rslts.pdf Results of the fit.
mismatch.data.txt Data on survival time following heart transplant.
glim.mismatch.fit.R R code to analyze the data.
mismatch.gamma.1.doc Results of the analysis.
exercise.2.rtf Exercise 2.
digamma.pdf Some graphs with the digamma function.
exercise.2.soln Solution to Exercise 2.
meron.analysis.1.R Code for the solution.
wald.score.lr.doc Graph showing the relationship between the LR, Wald and score tests.
exercise.3.rtf Exercise 3.
exercise.3.soln.R Code to solve Exercise 3.
exercise.3.soln.pdf And the results.
dist.examples.pdf Examples of distributions with their link functions. From McCullagh and Nelder
mc.int.exercise.pdf An exercise illustrating the difference between multicollinearity and interaction,
in the context of linear regression.
mc.int.soln.pdf Solution to the exercise.
exam.guidelines.pdf Guidelines for the exam.
past.exam.pdf A past exam.
exam.solution.pdf And its answers.
aic.examples.pdf Examples of model selection using AIC.
mismatch.lm.diagnostics.R Code to compute linear-model diagnostics for the mismatch data.
mismatch.glm.diagnostics.R Code to compute GLIM diagnostics for the mismatch data.
mismatch.diagnostics.rslts.1.pdf Diagnostics for the mismatch data.
mismatch.diagnostics.rslts.2.pdf More diagnostics.
overdispersion.examples.pdf Examples of overdispersion.
medfly.quasi.R Code to analyze the medfly data using quasi-likelihood.
medfly.quasi.rslts.pdf And the results.
For the exam
more.formulas.pdf An additional page of formulas which will be attached to the exam (together with those from Week 1).
moed.a.solution.pdf Solution to moed aleph.
moed.a.stem.leaf.pdf Stem-and-leaf diagram of grades for moed aleph.