Given a block of trials of an MLDS experiment, an underlying response function and the judgment variability, simulate the response of an observer.
1  SimMLDS(Trials, Scale, Sigma, n = 1)

Trials 
an N by 4 or 3 matrix or data frame of integers indicating the n trials of an MLDS experiment. The columns indicate the indices of the stimuli presented on a trial, 4 for an experiment with quadruples and 3 for triads. A data frame for this argument is most easily generated with the 
Scale 
a vector of values indicating the underlying responses of the simulated observer for each stimulus level. The length of this vector should equal the largest integer in 
Sigma 
a vector of length 1 indicating the judgment standard deviation of the simulated observer. 
n 
integer giving number of simulated data sets to return 
Given a data frame of indices to the responses associated with stimulus levels and the judgment variability, the function returns the results of 1 or multiple MLDS experiments, either with triads or quads, depending on the number of columns in the data frame.
If the argument n
is set to 1 (default), an object of class ‘mlds.df’ or ‘mlbs.df’ with simulated responses. If n
is greater than 1, a list of such objects is returned.
Kenneth Knoblauch and Laurence T. Maloney
Maloney, L. T. and Yang, J. N. (2003). Maximum likelihood difference scaling. Journal of Vision, 3(8):5, 573–585, http://journalofvision.org/3/8/5/, doi:10.1167/3.8.5.
Knoblauch, K. and Maloney, L. T. (2008) MLDS: Maximum likelihood difference scaling in R. Journal of Statistical Software, 25:2, 1–26, http://www.jstatsoft.org/v25/i02.
see also boot.mlds
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