mdprefmx {lazy.mdpref} | R Documentation |
Finite Mixture Model for MDPREF
mdprefmx(f, n, ij, subj, ndim = 2, nclass = 2, alpha = 1, init = 2, X = NULL, B = NULL, rho = NULL, estX = 1, estB = 1, estrho = 1, minp = 1e-07, lmax = 10, eps = 1e-06, lmax2 = 3, print = 1, plot = 0)
f |
vector consisting of the # of times that the left stimuli was chosen out of n trials. |
n |
vector consisting of the # of trials. |
ij |
matrix indicating the stimulus pair. |
subj |
vector indicating the subject. |
ndim |
# of dimensions |
nclass |
# of laten classes |
alpha |
hyper-parameter vector of size nclass for Dirichlet prior of rho |
init |
method for initial configuration |
X |
initial configuration, if any |
B |
initial configuration, if any |
rho |
initial configuration, if any |
estX |
= 0 to skip the estimation of X and fix it to the value given in X. |
estB |
= 0 to skip the estimation of B and fix it to the value given in B. |
estrho |
= 0 to skip the estimation of rho and fix it to the value given in rho. |
minp |
minimum value of the probability |
lmax |
max # of iterations |
eps |
criterion for convergence |
lmax2 |
max # of iterations for the inner iteration for X and Beta |
print |
= 1 to print the result |
plot |
= 1 to plot the result |
The quartet
( subj, n, f, ij ) contains the result of the paired comparison data.
Thoese four objects has the same length or # of rows.
The k-th elements of the quartet indicates that
subj[k] preferred stimulus ij[k,1] over ij[k,2] f[k] times when exposed
to the pair n[k] times.
The paired comparizon for each subject does no have to be complete.
ij <- cbind( data_comp$ij.1, data_comp$ij.2) mdprefmx( f=data_comp$f, n=data_comp$n, ij=ij, subj=data_comp$subj, plot=1 ) ij <- cbind( data_miss$ij.1, data_miss$ij.2) mdprefmx( f=data_miss$f, n=data_miss$n, ij=ij, subj=data_miss$subj, plot=1 )