bandwidth_plugin {modelfree}

Plug-in bandwidth for local polynomial estimator of a psychometric function

Description

The function calculates an estimate of the AMISE optimal bandwidth for a local polynomial estimate of the psychometric function.

Usage

bandwidth_plugin( r, m, x, link = "logit", guessing = 0,
                   lapsing = 0, K = 2, p = 1, ker = "dnorm" )

Arguments

r

number of successes at points x

m

number of trials at points x

x

stimulus levels

link

(optional) name of the link function to be used; default is "logit"

guessing

(optional) guessing rate; default is 0

lapsing

(optional) lapsing rate; default is 0

K

(optional) power parameter for Weibull and reverse Weibull link; default is 2

p

(optional) degree of the polynomial; default is 1

ker

(optional) kernel function for weights; default is "dnorm"

Value

⁠h ⁠ plug-in bandwidth (ISE optimal on eta-scale)

Examples

data("Miranda_Henson")
x = Miranda_Henson$x
r = Miranda_Henson$r
m = Miranda_Henson$m
numxfit <- 199; # Number of new points to be generated minus 1
xfit <- (max(x)-min(x)) * (0:numxfit) / numxfit + min(x)
# Find a plug-in bandwidth
bwd <- bandwidth_plugin( r, m, x)
pfit <- locglmfit( xfit, r, m, x, bwd )$pfit
# Plot the fitted curve
plot( x, r / m, xlim = c( 0.1, 1.302 ), ylim = c( 0.0165, 0.965 ), type = "p", pch="*" )
lines(xfit, pfit )