Hald

hald

The Hald data have been used in many
books and papers to illustrate variable selection. The data relate to an
engineering application that was concerned with the effect of the
composition of cement on heat evolved during hardening. The response
variable Y is the heat evolved in a cement mix. The four
explanatory variables are ingredients of the mix, X1:
tricalcium aluminate, X2: tricalcium silicate, X3:
tetracalcium alumino ferrite, X4: dicalcium silicate. An
important feature of these data is that the variables X1 and
 X3 are highly correlated, as well as the variables X2 and 
X4. Thus we should expect any subset of (X1,X2,X3,X4) 
that includes one variable from highly correlated pair to do as any subset that 
also includes the other member.

datasets

Package for Bayesian Model Averaging in linear models and
generalized linear models using stochastic or
deterministic sampling without replacement from posterior
distributions. Prior distributions on coefficients are
from Zellner's g-prior or mixtures of g-priors
corresponding to the Zellner-Siow Cauchy Priors or the
mixture of g-priors from
Liang et al (2008)
<http://dx.doi.org/10.1198/016214507000001337>
for linear models or mixtures of
g-priors in GLMs of Li and Clyde (2015)
<http://arxiv.org/abs/1503.06913>. Other model
selection criteria include AIC, BIC and Empirical Bayes estimates of g.
Sampling probabilities may be updated based on the sampled models
using Sampling w/out Replacement or an efficient MCMC algorithm
samples models using the BAS tree structure as an efficient
hash table. Uniform priors over all models or beta-binomial prior distributions on
model size are allowed, and for large p truncated priors on the model
space may be used. The user may force variables to always be included.
Details behind the sampling algorithm are provided in
Clyde, Ghosh and Littman (2010) <http://dx.doi.org/10.1198/jcgs.2010.09049>.

Merlise Clyde

Bayesian Model Averaging using Bayesian Adaptive Sampling

Hald function

<code>hald</code> is a dataframe with 13 observations and 5 variables
 (columns), Y: Heat evolved per gram of cement (in calories)
 X1: Amount of tricalcium aluminate
 X2: Amount of tricalcium silicate
 X3: Amount of tetracalcium alumino ferrite
 X4: Amount of dicalcium silicate

Format

Wood, H., Steinour, H.H., and Starke, H.R. (1932). "Effect of
  Composition of Portland cement on Heat Evolved During Hardening",
  Industrila and Engineering Chemistry, 24, 1207-1214.

Hald: Hald Data

Description

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