Data and Functions Used in Linear Models and Regression with R: An Integrated Approach
Basis of column space of a matrix
Convert categorical variable to several binary variables
Simultaneous confidence intervals in a linear model
Confidence interval for a linear parametric function in a linear model
Table of condition indices and singular vectors
Basis of orthogonal complement of column space of a matrix
Confidence ellipsiod for multiple parameters in a linear model.
Frobenius norm of a matrix
ANOVA table for linear hypothesis in a linear model
ANOVA table for adequacy of a subset in a linear model)
Testable and untestable hypotheses in linear model
Test of a linear hypothesis in a linear model
Basis of intersection of two column spaces
Whether one column space is contained in another
Intercept augmented variance inflation factors
Multiple comparison tests
Orthogonal projector of a matrix
Supplementary basis vectors for column space of a matrix
Trace of matrix
Prepare design matrix for two way layout with single oberservation per...
Prepare design matrix for balanced two way layout
Prepare design matrix for nested model with groups and subgroups
Data files and a few functions used in the book 'Linear Models and Regression with R: An Integrated Approach' by Debasis Sengupta and Sreenivas Rao Jammalamadaka (2019).