elementary.effects.lsd {LSDsensitivity}

Elementary effects sensitivity analysis

Description

This function performs the an elementary effects sensitivity analysis on the sample data produced by a LSD simulation model using the Morris (1991) one-at-a-time sampling method.

Usage

elementary.effects.lsd( data, p = 4, jump = 2 )

Arguments

data

an object created by a previous call to read.doe.lsd which contains all the required experimental data for the analysis.

p

integer: the number of levels of the DoE as set in LSD when the DoE was configured. The default is 4 (also the LSD default).

jump

integer: the size of the jump (increase/decrease) for each point change in the DoE as set in LSD when the DoE was configured. The default is 2 (also the LSD default).

Details

The elementary effects analysis statistics are only meaningful if the DoE was created using the Morris design, as when LSD EE Sampling... option is used to produce the DoE.

This function is a wrapper to the function morris in sensitivity-package.

Value

The function returns an object/list of class morris.lsd containing several items, among them:

table

the elementary effects sensitivity analysis results data.

The returned object can also be directly printed or plotted using plot() or any similar function. See the class morris for full details, as this class is equivalent to it.

Note

See the note in LSDsensitivity-package for step-by-step instructions on how to perform the complete sensitivity analysis process using LSD and R.

Author(s)

NA

References

Morris MD (1991) Factorial sampling plans for preliminary computational experiments.Technometrics 33(1):161-174

See Also

read.doe.lsd,

morris in sensitivity-package

Examples

# get the example directory name
path <- system.file( "extdata/ee", package = "LSDsensitivity" )

# Steps to use this function:
# 1. define the variables you want to use in the analysis
# 2. load data from a LSD simulation saved results using read.doe.lsd
# 3. perform the elementary effects analysis applying elementary.effects.lsd

lsdVars <- c( "var1", "var2", "var3" )         # the definition of existing variables

dataSet <- read.doe.lsd( path,                 # data files  folder
                         "Sim2",               # data files base name (same as .lsd file)
                         "var1",               # variable name to perform the sensitivity analysis
                         saveVars = lsdVars )  # LSD variables to keep in dataset

SA <- elementary.effects.lsd( dataSet,         # LSD experimental data set
                              p = 4,           # number of levels of the design (as set in LSD)
                              jump = 2 )       # number of jumps per level (as set in LSD)

print( SA )                                    # show analysis table
plot( SA )                                     # plot analysis chart