dae-package {dae}

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: 2024-06-12

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, main-plot 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) two-phase
	experiment
Oats.dat	Data for an experiment to investigate nitrogen response
	of 3 oats varieties
Sensory3Phase.dat	Data for the three-phahse sensory evaluation
	experiment in Brien, C.J. and Payne, R.W. (1999)
Sensory3PhaseShort.dat	Data for the three-phase 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 two-level 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 two-way 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 two-way grid using ggplot2.
Assessing designs:
designAmeasures	Calculates the A-optimality 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) two-phase,
	(ii) first-phase, (iii) cross-phase, treatments, and
	(iv) combined-units 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
	one-degree-of-freedom-test-for-nonadditivity
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
projector-class	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
show-methods	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/0000-0003-0581-1817>)

Maintainer: Chris Brien <[e-mail]>