Package: spnn
Type: Package
Title: Scale Invariant Probabilistic Neural Networks
Version: 1.3.0
Date: 2025-10-20
Author: Romin Ebrahimi [aut, cre]
Maintainer: Romin Ebrahimi <romin.ebrahimi@utexas.edu>
Authors@R: person(given = "Romin",
                  family = "Ebrahimi",
                  role = c("aut", "cre"),
                  email = "romin.ebrahimi@utexas.edu")
Description: Scale invariant version of the original PNN proposed by Specht (1990) <doi:10.1016/0893-6080(90)90049-q> with the added functionality of allowing for smoothing along multiple dimensions while accounting for covariances within the data set. It is written in the R statistical programming language. Given a data set with categorical variables, we use this algorithm to estimate the probabilities of a new observation vector belonging to a specific category. This type of neural network provides the benefits of fast training time relative to backpropagation and statistical generalization with only a small set of known observations.
License: GPL (>= 2)
Imports: MASS (>= 3.1-20), Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2025-10-20 16:04:46 UTC; rebrahimi
Repository: CRAN
Date/Publication: 2025-10-20 16:20:02 UTC
Built: R 4.6.0; aarch64-apple-darwin23; 2026-04-25 22:32:46 UTC; unix
Archs: spnn.so.dSYM
