binom_lims | R Documentation |
This function finds the maximum likelihood estimates of the parameters of the psychometric function with guessing and lapsing rates, only guessing rate, or only lapsing rate.
binom_lims( r, m, x, gl = "both", link = "logit", p = 1, K = 2, initval = NULL )
r |
number of successes at points x |
m |
number of trials at points x |
x |
stimulus levels |
gl |
(optional) indicator, calulate only guessing if "guessing", only lapsing if "lapsing" and both guessing and lapsing if "both"; default is "both" |
link |
(optional) name of the link function; default is "logit" |
p |
(optional) degree of the polynomial; default is 1 |
K |
(optional) power parameter for Weibull and reverse Weibull link; default is 2 |
initval |
(optional) initial value for guessing and lapsing; default is c(.01 .01) if guessing and rates are estimated, and .01 if only guessing or only lapsing rate is estimated |
b
estimated coefficients for the linear part
guessing
estimated guessing rate (if estimated)
lapsing
estimated lapsing rate (if estimated)
fit
glm object to be used in evaluation of fitted values
data("Baker_etal")
x = Baker_etal$x
r = Baker_etal$r
m = Baker_etal$m
plot( x, r / m, xlim = c( 0.16, 7.83 ), ylim = c( -0.01, 1.01 ), type = "p", pch="*" )
val <- binomfit_lims( r, m, x, link = "probit" )
numxfit <- 199; # Number of new points to be generated minus 1
xfit <- (max(x)-min(x)) * (0:numxfit) / numxfit + min(x)
# Plot the fitted curve
pfit<-predict( val$fit, data.frame( x = xfit ), type = "response" )
lines(xfit, pfit )
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