infoDecompuTE0.6.2 package

Information Decomposition of Two-Phase Experiments

getVMat.twoPhase

Get the Variance Matrices for Two-Phase experiment

identityMat

Identity Matrix

infoDecompMat

Construct the Matrix from Information Decomposition

infoDecompuTE-package

Information Decomposition of Two-phase Experiments

invInfMat

Invert the Information Matrix

J

Identity Matrix Minus Averaging Matrix

K

Averaging Matrix

makeBlkDesMat

Construct Block Design Matrix

makeContrMat

Make Contrast Matrix

makeOrthProjectors

Construct Orthogonal Projector Matrices

makeOverDesMat

Construct the Overall Treatment or Block design Matrix

projMat

Construct a Projection Matrix

summaryAovOnePhase

Summarize an Theoretical Analysis of Variance Model of Single-Phase Ex...

summaryAovTwoPhase

Summarize an Theoretical Analysis of Variance Model of Two-Phase Exper...

getFixedEF.onePhase

Get the Fixed Components' coefficients and Efficiency Factors of Singl...

getFixedEF.twoPhase

Get the Fixed Components' coefficients and Efficiency Factors of Two-P...

getTrtCoef

Get the Treatment Coefficients

toLatexTable

Convert the R output to Latex Table

tr

Trace of the Matrix

unity

Construct a unity vector

getTrtRep

Calculate the Treatment Replication number

adjustEffectNames

Adjust the Effects' Names

adjustMissingLevels

Adjust the Missing Levels

getCoefVC.onePhase

Get Variance Components' Coefficients and Mean Squares for Single-Phas...

getCoefVC.twoPhase

Get Variance Components' Coefficients and Mean Squares for Single-Phas...

getEffFactor

Construct the Matrix from Information Decomposition and Compute the Ef...

getVMat.onePhase

Get the Variance Matrices for Single-Phase experiment

The main purpose of this package is to generate the structure of the analysis of variance (ANOVA) table of the two-phase experiments. The user only need to input the design and the relationships of the random and fixed factors using the Wilkinson-Rogers' syntax, this package can then quickly generate the structure of the ANOVA table with the coefficients of the variance components for the expected mean squares. Thus, the balanced incomplete block design and provides the efficiency factors of the fixed effects can also be studied and compared much easily.

  • Maintainer: Kevin Chang
  • License: GPL (>= 3)
  • Last published: 2020-03-28