lpois: Likelihoods for Poisson and Gaussian psychometric functions
In MPDiR: Data sets and scripts for Modeling Psychophysical Data in R.

Description Usage Arguments Details Value Author(s) See Also Examples

These functions define likelihoods for binomial models with Gaussian or Poisson psychometric functions.

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lpois(p, d)
lpois1(q, p, d)
lnorm(p, d)

`p`	numeric vector of parameters (in `lpois` and `lnorm`) or fixed Poisson parameter (`lpois2`).
`d`	data frame with number of correct (`nyes`) and incorrect (`nno`) responses and intensity levels (`Q`)
`q`	numeric vector of length 1 giving scale parameter (`lpois2`)

These functions calculate the log likelihood for binomial models with Gaussian or Poisson psychometric functions and can be used with optim to find the best parameters.

Returns a numeric value giving minus the log likelihood for the given model.

Kenneth Knoblauch

See optim

data(HSP)
SHR2 <- subset(HSP, Obs == "SH" & Run == "R2")
SHR2 <- within(SHR2, {
	nyes <- N * p/100
	nno <- N - nyes
	})
optim(par = c(5, 0.35), lnorm, d = SHR2)