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dae (version 3.2.21)

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 .

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install.packages('dae')

Monthly Downloads

1,095

Version

3.2.21

License

GPL (>= 2)

Maintainer

Chris Brien

Last Published

January 14th, 2024

Functions in dae (3.2.21)

Sensory3Phase.dat

Data for the three-phase sensory evaluation experiment in Brien, C.J. and Payne, R.W. (1999)

Deprecated Functions in Package dae

tools:::Rd_package_title("dae")

Calculates the design matrix for fitting the random component of a natural cubic smoothing spline

The intermittent, randomly-presented, startup tips.

correct.degfree

Check the degrees of freedom in an object of class projector

Examines the relationship between the eigenvectors for two decompositions

as.data.frame.pstructure

Coerces a pstructure.object to a data.frame.

Convert a factor to a numeric vector

blockboundaryPlot

This function plots a block boundary on a plot produced by designPlot.

designAmeasures

Calculates the average variance of pairwise differences from the variance matrix for predictions

Degrees of freedom extraction and replacement

designBlocksGGPlot

Adds block boundaries to a plot produced by designGGPlot.

Plots labels on two-way grids of coloured cells using ggplot2 to represent an experimental design

designPlotlabels

Plots labels on a two-way grid using ggplot2

designLatinSqrSys

Generate a systematic plan for a Latin Square 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.

A graphical representation of an experimental design using labels stored in a matrix.

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.

designRandomize

Randomize allocated to recipient factors to produce a layout for an experiment

Computes the detectable difference for an experiment

Divides a factor into several separate factors

Expands the values in table to a vector

Combines several factors into one

Generate all combinations of several factors and, optionally, replicate them

Extracts the canonical efficiency factors from a pcanon.object or a p2canon.object.

efficiency.criteria

Computes efficiency criteria from a set of efficiency factors

forms the ar1 correlation matrix for a (generalized) factor

Generate all combinations of the levels of the supplied factors, without replication

Splits a factor whose levels consist of several delimited strings into several factors

Extract the elements of an array specified by the subscripts

fac.multinested

Creates several factors, one for each level of nesting.fac and each of whose values are either generated within those of a level of nesting.fac or using the values of nested.fac within a levels of nesting.fac.

creates a factor, the nested factor, whose values are generated within those of the factor nesting.fac

computes the summation matrix that produces sums corresponding to a (generalized) factor

Recasts a factor by modifying the values in the factor vector and/or the levels attribute, possibly combining some levels into a single level.

Cleaves a single factor, each of whose levels has delimited strings, into several factors using the separated strings.

Forms a two-level factor from a logical object.

forms the variance matrix for the variance component of a (generalized) factor

Calcuates the harmonic mean.

Recodes factor levels using values in a vector. The values in the vector do not have to be unique.

Extract the fitted values for a fitted model

Extracts the marginality matrix (matrices) from a pstructure.object or a pcanon.object.

Match, for each combination of a set of columns in x, the row that has the same combination in table

Forms the direct product of two matrices

Forms a unit matrix

computes the projection matrix that produces means

interaction.ABC.plot

Plots an interaction plot for three factors

Forms the direct sum of a list of matrices

Forms a correlation matrix in which all correlations have the same value.

get.daeTolerance

Gets the value of daeTolerance for the package dae

Forms an arma correlation matrix

Forms an ar2 correlation matrix

Form a banded matrix from a vector of values

generates a vector of random values from a multivariate normal distribution

Tests whether all elements are approximately zero

Converts the first two levels of a factor into the numeric values -1 and +1

Tests whether an object is a valid object of class projector

set.daeTolerance

Sets the values of daeTolerance for the package dae

Extract the fitted values for a fitted model from an aovlist object

Forms a general correlation matrix

Calculates the variances of a set of predicted effects from a mixed model, based on supplied matrices or formulae.

Forms an ma2 correlation matrix

Forms a square matrix of ones

Computes the number of replicates for an experiment

Forms an ar1 correlation matrix

Calculates the variances of a set of predicted effects from a mixed model

Forms an exponential correlation matrix

Computes the generalized inverse of a matrix

Forms an exponential correlation matrix

Forms an ar3 correlation matrix

Calculates the variance matrix of the random effects for a natural cubic smoothing spline

Forms an ma1 correlation matrix

Description of a p2canon object

Print an aliasing data.frame

projector-class

Class projector

Calculates the variance matrix for the random effects from a mixed model, based on a supplied formula or a matrix.

Description of a pcanon object

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.

Create projectors

Forms an sar correlation matrix

Forms an sar2 correlation matrix

Computes the power for an experiment

computes the projection matrix that produces means

A canonical analysis of the relationships between two sets of projectors

print.projector

Print projectors

print.summary.pcanon

Prints the values in an summary.pcanon object

Compute the projection and Residual operators for two, possibly nonorthogonal, projectors

projs.combine.p2canon

Extract, from a p2canon object, the projectors that give the combined canonical decomposition

Methods for Function show in Package dae

proj2.efficiency

Computes the canonical efficiency factors for the joint decomposition of two projectors

Half or full normal plot of Yates effects

Performs Tukey's one-degree-of-freedom-test-for-nonadditivity

Extract Yates effects

Generate paper strength values

print.pstructure

Prints a pstructure.object

summary.p2canon

Summarize a canonical analysis of the relationships between two sets of projectors

Summarizes the anatomy of a design, being the decomposition of the sample space based on its canonical analysis, as produced by designAnatomy

print.summary.p2canon

Prints the values in an summary.p2canon object

Canonical efficiency factors and eigenvectors in joint decomposition of two projectors

Extract the residuals for a fitted model

pstructure.formula

Takes a formula and constructs a pstructure.object that includes the orthogonalized projectors for the terms in a formula

Replicate the rows of a data.frame by repeating each row consecutively and/or repeating all rows as a group

pstructure.object

Description of a pstructure object

residuals.aovlist

Extract the residuals from an aovlist object

Exp249.munit.des

Systematic, main-unit design for an experiment to be run in a greenhouse

Data for an experiment to investigate the effects of grazing patterns on pasture composition

A design for one of the growth cabinets in an experiment with 50 lines and 4 harvests

Data for a 2^4 factorial experiment

Data for a balanced incomplete block experiment

ABC.Interact.dat

Randomly generated set of values indexed by three factors

McIntyreTMV.dat

The design and data from McIntyre's (1955) two-phase experiment

Data for an experiment to investigate nitrogen response of 3 oats varieties

Data for an experiment with rows and columns from Williams (2002)

LatticeSquare_t49.des

A Lattice square design for 49 treatments