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: 2026-09-15 07:31:15 UTC; root
Repository: https://romin-ebrahimi.r-universe.dev
Date/Publication: 2025-10-20 16:06:46 UTC
RemoteUrl: https://github.com/romin-ebrahimi/spnn
RemoteRef: HEAD
RemoteSha: c14af439b929ccd4cc3e50f8793920fb66862e60