analysis.anoasg {multisensi}

Runs a series of analyses of variance

Description

The analysis.anoasg function runs a series of analyses of variance on the columns of a data.frame, by using the aov function.

Usage

analysis.anoasg(Y, plan, nbcomp = 2, sigma.car = NULL,
                analysis.args = list(formula = 2,
                                     keep.outputs = FALSE))

Arguments

Y

a data.frame of output variables or principal components.

plan

a data.frame containing the design.

nbcomp

the number of Y variables to analyse (the first nbcomp variables of Y will be analysed).

sigma.car

NULL or sum of squares of Y. If not NULL, compute the Generalised Sensitivity Indices (saved in the last column of the data.frame mSI/tSI/iSI outputs.

analysis.args

a list of arguments. The formula component is for ANOVA formula like "A+B+c+A:B" OR an integer giving the maximum interaction order (1 for main effects). If it contains keep.outputs=TRUE, the outputs associated with the analysis of each variable are returned (see section Value).

Value

A list containing:

SI

data.frame of sensitivity indices

mSI

data.frame of first-order sensitivity indices

tSI

data.frame of total sensitivity indices

iSI

data.frame of interaction sensitivity indices

inertia

vector of Inertia explained by the variables

indic.fact

0-1 matrix to indicate the factors associated with each factorial effect

Hpredict

prediction of outputs

outputkept

if analysis.args$keep.outputs=TRUE, list of the outputs returned by the sensitivity analysis performed on each variable

call.info

list with first element analysis="anova"

See Also

aov

Examples

# Test case : the Winter Wheat Dynamic Models (WWDM)
#  input factors design
 data(biomasseX)
# output variables (precalculated to speed up the example)
 data(biomasseY)

 res <- analysis.anoasg(biomasseY, biomasseX, 
                        nbcomp = 2, sigma.car = NULL,
                        analysis.args = list(formula = 2,
                                             keep.outputs = FALSE))