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dae (version 3.2-10)

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

install.packages('dae')

Monthly Downloads

1,095

Version

3.2-10

License

GPL (>= 2)

Maintainer

Chris Brien

Last Published

August 6th, 2021

Functions in dae (3.2-10)

Data for a balanced incomplete block experiment

LatticeSquare_t49.des

A Lattice square design for 49 treatments

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

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 the effects of grazing patterns on pasture composition

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

Exp249.munit.des

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

Data for a 2^4 factorial experiment

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

blockboundaryPlot

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

correct.degfree

Check the degrees of freedom in an object of class projector

Deprecated Functions in Package dae

Sensory3Phase.dat

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

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

Examines the relationship between the eigenvectors for two decompositions

The intermittent, randomly-presented, startup tips.

as.data.frame.pstructure

Coerces a pstructure.object to a data.frame.

Convert a factor to a numeric vector

Degrees of freedom extraction and replacement

designAmeasures

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

designPlotlabels

Plots labels on a two-way grid using ggplot2

designRandomize

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

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

Plots labels on two-way grids of coloured cells using ggplot2

designLatinSqrSys

Generate a systematic plan for a Latin Square design

designBlocksGGPlot

Adds block boundaries to a plot produced by designGGPlot.

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.

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

Combines several factors into one

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

Extract the elements of an array specified by the subscripts

efficiency.criteria

Computes efficiency criteria from a set of efficiency factors

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

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.

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

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

Divides a factor into several individual factors

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

Forms a two-level factor from a logical object.

Computes the detectable difference for an experiment

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

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

forms the ar1 correlation matrix for a (generalized) factor

Expands the values in table to a vector

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

computes the projection matrix that produces means

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

Tests whether all elements are approximately zero

interaction.ABC.plot

Plots an interaction plot for three factors

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

get.daeTolerance

Gets the value of daeTolerance for the package dae

Forms an ar3 correlation matrix

Forms a unit matrix

Forms an arma correlation matrix

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

Tests whether an object is a valid object of class projector

Forms an exponential correlation matrix

Forms an ma2 correlation matrix

Forms the direct sum of a list of matrices

Calcuates the harmonic mean.

Form a banded matrix from a vector of values

Extract the fitted values for a fitted model

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

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

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

print.pstructure

Prints a pstructure.object

print.projector

Print projectors

Description of a p2canon object

computes the projection matrix that produces means

Forms an sar2 correlation matrix

Forms a square matrix of ones

Computes the number of replicates for an experiment

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

Description of a pcanon object

Forms the direct product of two matrices

print.summary.pcanon

Prints the values in an summary.pcanon object

print.summary.p2canon

Prints the values in an summary.p2canon object

projs.combine.p2canon

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

projector-class

Class projector

Canonical efficiency factors and eigenvectors in joint decomposition of two projectors

Forms an sar correlation matrix

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

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

pstructure.formula

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

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

Half or full normal plot of Yates effects

set.daeTolerance

Sets the values of daeTolerance for the package dae

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

Methods for Function show in Package dae

proj2.efficiency

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

pstructure.object

Description of a pstructure object

summary.p2canon

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

Generate paper strength values

Create projectors

Extract Yates effects

A canonical analysis of the relationships between two sets of projectors

Computes the power for an experiment

Forms an exponential correlation matrix

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

Forms an ar2 correlation matrix

Forms an ma1 correlation matrix

Forms an ar1 correlation matrix

Extract the residuals for a fitted model

residuals.aovlist

Extract the residuals from an aovlist object

Print an aliasing data.frame

generates a vector of random values from a multivariate normal distribution