variableNames(nEnvFactors, envFactorNames=NULL)nEnvFactors is 1 and the number of levels for the enviromental factor
(nLevels)is 1, there is one condition in the experiment (i.e. no
envirenvFactorNames <- c( "Temperature", "Dosage" )
Default = NULLnEnvFactors = 1 and nLevels = 1, there is no environmetal pertubation in the experimental.
Then we re-define nEnvFactors to be 0 within the algorithm. Accordingly, variableNumber = 1, and
variableNames is one genetic factor "Q".
When nEnvFactors = 1, variableNumber = 3, and
variableNames are one genetic factor "Q", one environmental factor "F",
and one interacting factor "QxF".
When nEnvFactors = 2, variableNumber = 7, and variableNames are one genetic factor "Q",
two environmental factors "F1" and "F2",
three two-way interacting factors "QF1", "QF2", "F1F2",
and one three way interacting factors "QxF1xF2".
When nEnvFactors = 3, variableNumber = 15, and
variableNames are one genetic factor "Q",
three environmental factors "F1", "F2" and "F3",
six two-way interacting factors "QF1", "QF2", "QF3", "F1F2",
"F2F3" and "F1F3",
four three-way interacting factors "QxF1xF2", "QxF1xF3",
"QxF2xF3", "F1xF2xF3"
and one four-way interacting factors "QxF1xF2xF3".variableNumber