fitLSDT: Run the non-linear regression on a data table

In VinLaflamme/nlregVL: Non-linear fits for psychometric functions

Description

Run the non-linear regression on a data table

Usage

fitLSDT(dataF, cD, cNbS, cNbL, cBy, type = "CG", control, residFun, getPred,
  fnJacob, fnStart, rpsyF = T)

Arguments

dataF	The data table containing the data to be fitted
cD	name (or position) of the column containing the x-axis data. In the case of a temporal bisection task, this corresponds to the name (or position) of the column containing the duration.
cNbS	name (or position) of the column containing the number of "short" responses.
cBy	name (or position) of the column(s) to group by. If left empty, it will take all other columns.
type	string expliciting which of three available fitting functions will be used. "CG" for cumulative Gaussian, "LN" for lognormal and "PL" for pseudologistic.
control	a control list for the non linear regression. See nls.lm.control
residFun	Function that returns the residuals.
getPred	Function that returns the predicted value.
fnJacob	Function that returns the jacobian of the function to be fitted.
fnStart	Function that returns the starting parameters.
rpsyF	Return psyF object as a column?
CNbL	name (or position) of the column containing the number of "long" responses.

Value

A data.table with the parameter estimates, their confidence interval, the R square statistic and the Chi square statistic.

See Also

psyFitted-class

Examples

data("exampleData",package="nlregVL")
result<-nlregVL::fitLSDT(dataF = exampleData,cD = "Duration",cNbS = "Nb1",cNbL = "Nb3",cBy = "Sub")

VinLaflamme/nlregVL documentation built on May 30, 2019, 2:04 a.m.