Nonparametric Item Response Theory

Fits nonparametric item and option characteristic curves using kernel smoothing. It allows for optimal selection of the smoothing bandwidth using cross-validation and a variety of exploratory plotting tools. The kernel smoothing is based on methods described in Silverman, B.W. (1986). Density Estimation for Statistics and Data Analysis. Chapman & Hall, London.


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install.packages("KernSmoothIRT")

6.4 by Brian McGuire, a year ago


Browse source code at https://github.com/cran/KernSmoothIRT


Authors: Angelo Mazza , Antonio Punzo , Brian McGuire


Documentation:   PDF Manual  


Task views:


GPL-2 license


Imports Rcpp, plotrix, rgl, methods

Linking to Rcpp


See at CRAN