daepackage {dae}  R Documentation 
Functions Useful in the Design and ANOVA of Experiments
Description
The content falls into the following groupings: (i) Data, (ii) Factor manipulation functions, (iii) Design functions, (iv) ANOVA functions, (v) Matrix functions, (vi) Projector and canonical efficiency functions, and (vii) Miscellaneous functions. There is a vignette describing how to use the design functions for randomizing and assessing designs available as a vignette called 'DesignNotes'. The ANOVA functions facilitate the extraction of information when the 'Error' function has been used in the call to 'aov'. The package 'dae' can also be installed from <http://chris.brien.name/rpackages/>.
Version: 3.2.28
Date: 20240612
Index
(i) Data  
ABC.Interact.dat
 Randomly generated set of values indexed by 
three factors  
BIBDWheat.dat
 Data for a balanced incomplete block experiment 
Casuarina.dat
 Data for an experiment with rows and columns from 
Williams (2002)  
Exp249.munit.des
 Systematic, mainplot design for an experiment to be 
run in a greenhouse  
Fac4Proc.dat
 Data for a 2^4 factorial experiment 
LatticeSquare_t49.des
 A Lattice square design for 49 treatments 
McIntyreTMV.dat
 The design and data from McIntyre (1955) twophase 
experiment  
Oats.dat
 Data for an experiment to investigate nitrogen response 
of 3 oats varieties  
Sensory3Phase.dat
 Data for the threephahse sensory evaluation 
experiment in Brien, C.J. and Payne, R.W. (1999)  
Sensory3PhaseShort.dat
 Data for the threephase sensory evaluation 
experiment in Brien, C.J. and Payne, R.W. (1999),  
but with short factor names  
SPLGrass.dat
 Data for an experiment to investigate the 
effects of grazing patterns on pasture  
composition  
(ii) Factor manipulation functions  
Forms a new or revised factor:  
fac.combine
 Combines several factors into one 
fac.multinested
 Creates several factors, one for each level of a nesting.fac 
and each of whose values are either generated within  
those of the level of nesting.fac or using the values  
of a nested.fac  
fac.nested
 Creates a factor, the nested factor, whose values are 
generated within those of a nesting factor  
fac.recast
 Recasts a factor by modifying the values in the factor vector 
and/or the levels attribute, possibly combining  
some levels into a single level.  
fac.recode
 Recodes factor 'levels' using possibly nonunique 
values in a vector. (May be deprecated in future.)  
fac.uselogical
 Forms a twolevel factor from a logical object 
mpone
 Converts the first two levels of a factor into 
the numeric values 1 and +1  
Forms multiple new factors:  
fac.divide
 Divides a factor into several separate factors 
fac.gen
 Generate all combinations of several factors and, 
optionally, replicate them  
fac.genfactors
 Generate all combinations of the levels of the supplied 
factors, without replication  
fac.split
 Splits a factor whose levels consist of several delimited 
strings into several factors.  
fac.uncombine
 Cleaves a single factor, each of whose levels has delimited 
strings, into several factors using the separated strings.  
Operates on factors:  
as.numfac
 Convert a factor to a numeric vector 
fac.match
 Match, for each combination of a set of columns 
in 'x', the row that has the same combination  
in 'table'  
(iii) Design functions  
Designing experiments:  
designLatinSqrSys
 Generate a systematic plan for a Latin Square design. 
designRandomize
 Randomize allocated to recipient factors to produce 
a layout for an experiment. It supersedes fac.layout . 

no.reps
 Computes the number of replicates for an experiment 
detect.diff
 Computes the detectable difference for an experiment 
power.exp
 Computes the power for an experiment 
Plotting designs:  
blockboundaryPlot
 This function plots a block boundary on a plot 
produced by 'designPlot'. It supersedes  
blockboundary.plot.  
designBlocksGGPlot
 Adds block boundaries to a plot produced by designGGPlot . 
designGGPlot
 Plots labels on a twoway grid of coloured cells using ggplot2 
to represent an experimental design.  
designPlot
 A graphical representation of an experimental design 
using labels stored in a matrix.  
It superseded design.plot.  
designPlotlabels
 Plots labels on a twoway grid using ggplot2 . 
Assessing designs:  
designAmeasures
 Calculates the Aoptimality measures from the 
variance matrix for predictions.  
designAnatomy
 Given the layout for a design, obtain its anatomy via 
the canonical analysis of its projectors to show the  
confounding and aliasing inherent in the design.  
designTwophaseAnatomies
 Given the layout for a design and three structure formulae, 
obtain the anatomies for the (i) twophase,  
(ii) firstphase, (iii) crossphase, treatments, and  
(iv) combinedunits designs.  
marginality.pstructure
 Extracts the marginality matrix from a 
pstructure.object 

marginality.pstructure
 Extracts a list containing the marginality matrices from 
a pcanon.object 

print.aliasing
 Prints an aliasing data.frame 
summary.pcanon
 Summarizes the anatomy of a design, being the 
decomposition of the sample space based on its  
canonical analysis.  
(iv) ANOVA functions  
fitted.aovlist
 Extract the fitted values for a fitted model 
from an aovlist object  
fitted.errors
 Extract the fitted values for a fitted model 
interaction.ABC.plot
 Plots an interaction plot for three factors 
qqyeffects
 Half or full normal plot of Yates effects 
resid.errors
 Extract the residuals for a fitted model 
residuals.aovlist
 Extract the residuals from an aovlist object 
strength
 Generate paper strength values 
tukey.1df
 Performs Tukey's 
onedegreeoffreedomtestfornonadditivity  
yates.effects
 Extract Yates effects 
(v) Matrix functions  
Operates on matrices:  
elements
 Extract the elements of an array specified by 
the subscripts  
mat.dirprod
 Forms the direct product of two matrices 
mat.dirsum
 Forms the direct sum of a list of matrices 
mat.ginv
 Computes the generalized inverse of a matrix 
Zncsspline
 Forms the design matrix for fitting the 
random effects for a natural cubic smoothing  
spline.  
Compute variance matrices for  
supplied variance component values:  
mat.random
 Calculates the variance matrix for the 
random effects from a mixed model, based  
on a formula or a supplied matrix  
mat.Vpred
 Forms the variance matrix of predictions 
based on supplied matrices  
mat.Vpredicts
 Forms the variance matrix of predictions, 
based on supplied matrices or formulae.  
Forms matrices using factors  
stored in a data.frame:  
fac.ar1mat
 Forms the ar1 correlation matrix for a 
(generalized) factor  
fac.sumop
 Computes the summation matrix that produces 
sums corresponding to a (generalized) factor  
fac.vcmat
 Forms the variance matrix for the variance 
component of a (generalized) factor  
Forms patterned matrices:  
mat.I
 Forms a unit matrix 
mat.J
 Forms a square matrix of ones 
mat.ncssvar
 Forms a variance matrix for random cubic 
smoothing spline effects  
Forms correlation matrices:  
mat.cor
 Forms a correlation matrix in which all 
correlations have the same value  
mat.corg
 Forms a general correlation matrix in which 
all correlations have different values  
mat.ar1
 Forms an ar1 correlation matrix 
mat.ar2
 Forms an ar2 correlation matrix 
mat.ar3
 Forms an ar3 correlation matrix 
mat.arma
 Forms an arma correlation matrix 
mat.banded
 Forms a banded matrix 
mat.exp
 Forms an exponential correlation matrix 
mat.gau
 Forms a gaussian correlation matrix 
mat.ma1
 Forms an ma1 correlation matrix 
mat.ma2
 Forms an ma2 correlation matrix 
mat.sar
 Forms an sar correlation matrix 
mat.sar2
 Forms an sar2 correlation matrix 
(vi) Projector and canonical efficiency functions  
Projector class:  
projector
 Create projectors 
projectorclass
 Class projector 
is.projector
 Tests whether an object is a valid object of 
class projector  
print.projector
 Print projectors 
correct.degfree
 Check the degrees of freedom in an object of 
class projector  
degfree
 Degrees of freedom extraction and replacement 
Accepts two or more formulae:  
designAnatomy
 An anatomy of a design, obtained from 
a canonical analysis of the relationships  
between sets of projectors.  
summary.pcanon
 Summarizes the anatomy of a design, being the 
decomposition of the sample space based on its  
canonical analysis  
print.summary.pcanon
 Prints the values in an 'summary.pcanon' object 
efficiencies.pcanon
 Extracts the canonical efficiency factors from a 
list of class 'pcanon'  
Accepts exactly two formulae:  
projs.2canon
 A canonical analysis of the relationships between 
two sets of projectors  
projs.combine.p2canon
 Extract, from a p2canon object, the projectors 
summary.p2canon
 A summary of the results of an analysis of 
the relationships between two sets of projectors  
print.summary.p2canon
 Prints the values in an 'summary.p2canon' object 
that give the combined decomposition  
efficiencies.p2canon
 Extracts the canonical efficiency factors from 
a list of class 'p2canon'  
Accepts a single formula:  
as.data.frame.pstructure
 Coerces a pstructure.object to a data.frame 
print.pstructure
 Prints a pstructure.object 
pstructure.formula
 Takes a formula and constructs a pstructure.object 
that includes the orthogonalized projectors for the  
terms in a formula  
porthogonalize.list
 Takes a list of projectors and constructs 
a pstructure.object that includes projectors, 

each of which has been orthogonalized to all projectors  
preceding it in the list.  
Others:  
decomp.relate
 Examines the relationship between the 
eigenvectors for two decompositions  
efficiency.criteria
 Computes efficiency criteria from a set of 
efficiency factors  
fac.meanop
 Computes the projection matrix that produces means 
proj2.eigen
 Canonical efficiency factors and eigenvectors 
in joint decomposition of two projectors  
proj2.efficiency
 Computes the canonical efficiency factors for 
the joint decomposition of two projectors  
proj2.combine
 Compute the projection and Residual operators 
for two, possibly nonorthogonal, projectors  
showmethods
 Methods for Function 'show' in Package dae 
(vii) Miscellaneous functions  
extab
 Expands the values in table to a vector 
get.daeRNGkind
 Gets the value of daeRNGkind for the package dae from 
the daeEnv environment.  
get.daeTolerance
 Gets the value of daeTolerance for the package dae. 
harmonic.mean
 Calcuates the harmonic mean. 
is.allzero
 Tests whether all elements are approximately zero 
rep.data.frame
 Replicate the rows of a data.frame by repeating 
each row consecutively and/or repeating all rows  
as a group.  
rmvnorm
 Generates a vector of random values from a 
multivariate normal distribution  
set.daeRNGkind
 Sets the values of daeRNGkind for the package dae in 
the daeEnv environment'  
set.daeTolerance
 Sets the value of daeTolerance for the package dae. 
Author(s)
Chris Brien [aut, cre] (<https://orcid.org/0000000305811817>)
Maintainer: Chris Brien <chris.brien@adelaide.edu.au>