ch.pHVOfit: Fits the p(HVO) function for the choice experiment

In ccpluncw/ccpl_R_chutils:

Fits the p(HVO) function for the choice experiment

Description

This function fits p(HVO) as a non-linear exponential decay function of an x variable (often overlap). It forces the first point to equal 1 and the last point is .5 on the y-axis. It outputs the fit of the function and the r_square.

Usage

ch.pHVOfit(x, y, grp = NULL, useTwoParameterModel = FALSE)

Arguments

x	the x variable for the x-axis (often overlap).
y	the y variable for the y-axis (often p(hit)).
grp	the grouping variable that identifies those stimuli whose value are above the reference distribution and those that are below the reference distribution. When this variable is included and useTwoParameterModel is set to TRUE, then the alpha parameter will be fit so it is symetric above and below 0.5 for refHVO and refLVO. DEFAULT = NULL (the grouping variable is ignored)
useTwoParameterModel	A boolean that specifies whether to use a two parameter model. If this is set to TRUE, then this function will fit a model whereby the rightmost point (overlap = 1.0) is not fixed at p(HVO) = 0.5. DEFAULT = FALSE.

Value

a list of the fit, r2 from the nls .

Examples

ch.pHVOfit (x,y, grp)

ccpluncw/ccpl_R_chutils documentation built on Feb. 28, 2024, 1:17 a.m.