Modelfree estimation of a psychometric function 


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bandwidth_cross_validation
h = bandwidth_cross_validation(r,m,x,H,link,guessing,lapsing,K,p,ker,maxiter,tol,method)
Crossvalidation bandwidth for a local polynomial estimate of the psychometric function with specified guessing and lapsing rates.
Input:
r
: number of successes at pointsx
m
: number of trials at pointsx
x
: stimulus levels
H
: search intervalOptional input:
link
: name of the link function; default is 'logit
'
guessing
: guessing rate; default is 0
lapsing
: lapsing rate; default is 0
K
: power parameter for Weibull and reverse Weibull link; default is 2
p
: degree of the polynomial; default is 1
ker
: kernel function for weights; default is 'normpdf
'
maxiter
: maximum number of iterations in Fisher scoring; default is 50
tol
: tolerance level at which to stop Fisher scoring; default is 1e6
method
: loss function to be used in crossvalidation: choose from: 'ISEeta
', 'ISE
', 'deviance
'; by default all possible values are calculatedOutput:
h
: crossvalidation bandwidth for the chosenmethod
; if nomethod
is specified, then it is threerow vector with entries corresponding to the estimated bandwidths on a pscale, on an etascale and for deviance