cement

This data set illustrates the heat expended (calories) from mixtures of four
different ingredients of Portland cement expressed as a percentage by weight.

datasets

This package includes functions to create model selection
        tables based on Akaike's information criterion (AIC) and the
        second-order AIC (AICc), as well as their quasi-likelihood
        counterparts (QAIC, QAICc).  Tables are printed with delta AIC
        and Akaike weights.  The package also includes functions to
        conduct model averaging (multimodel inference) for a given
        parameter of interest or predicted values.  Other handy
        functions enable the computation of relative variable
        importance, evidence ratios, and confidence sets for the best
        model.  The present version works with linear models ('lm'
        class), generalized linear models ('glm' class), linear mixed
        models ('lme' class), multinomial and ordinal logistic
        regressions ('multinom' and 'polr' classes).

Marc J Mazerolle

AICcmodavg

Model selection and multimodel inference based on (Q)AIC(c)

cement function

Burnham, K. P., Anderson, D. R. (2002) Model Selection and
 Multimodel Inference: a practical information-theoretic
 approach. Second edition. Springer: New York. Woods, H., Steinour, H. H., Starke, H. R. (1932) Effect of composition
 of Portland cement on heat evolved during hardening. Industrial
 and Engineering Chemistry 24, 1207--1214.

State of Data and AI Literacy Report 2025

cement: Heat expended following hardening of Portland cement.

Description

Usage

Arguments

source

Details

Examples