dae-package {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: 3.2-13

Date: 2021-11-15

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
as.numfac Convert a factor to a numeric vector
fac.combine Combines several factors into one
fac.divide Divides a factor into several individual factors
fac.gen Generate all combinations of several factors and,
optionally, replicate them
fac.gen Generate all combinations of the levels of the supplied
factors, without replication
fac.match Match, for each combination of a set of columns
in 'x', the row that has the same combination
in 'table'
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.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.
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
(iii) Design functions
blockboundaryPlot This function plots a block boundary on a plot
produced by 'designPlot'. It supersedes
blockboundary.plot.
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.
designBlocksGGPlot Adds block boundaries to a plot produced by designGGPlot.
designGGPlot Plots labels on a two-way grid of coloured cells using ggplot2.
designLatinSqrSys Generate a systematic plan for a Latin Square 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.
designRandomize Randomize allocated to recipient factors to produce
a layout for an experiment. It supersedes fac.layout.
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
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
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
elements Extract the elements of an array specified by
the subscripts
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
mat.I Forms a unit matrix
mat.J Forms a square matrix of ones
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.ncssvar Forms a variance matrix for random cubic
smoothing spline effects
mat.sar Forms an sar correlation matrix
mat.sar2 Forms an sar2 correlation matrix
mat.dirprod Forms the direct product of two matrices
mat.dirsum Forms the direct sum of a list of matrices
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
mat.Vpredicts Forms the variance matrix of predictions,
based on supplied matrices or formulae.
Zncsspline Forms the design matrix for fitting the
random effects for a natural cubic smoothing
spline.
(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
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.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.daeTolerance Sets the value of daeTolerance for the package dae

Author(s)

NA

Maintainer: NA


[Package dae version 3.2-13 Index]