DESCRIPTION

Package: PSOBrainModeler
Type: Package
Title: Particle Swarm Optimization-Based Hyperparameter Tuning for Support Vector
  Regression Models in Cerebral Autoregulation Analysis
Version: 0.5.2
Authors@R: c(
    person("Benjamin", "Jorquera", email = "benjamin.jorquera@usach.cl", role = c("aut", "cre")),
    person("Jose Luis", "Jara", email = "jljara@usach.cl", role = "aut")
  )
Maintainer: Benjamin Jorquera <benjamin.jorquera@usach.cl>
Description: This package offers a comprehensive toolkit for the analysis and
  modeling of biological signal data specific to individual patients. It facilitates
  the training of Support Vector Regression (SVR) models to represent and predict
  cerebral autoregulation phenomena. Utilizing blocked k-fold cross-validation,
  the package conducts hyperparameter optimization through Particle Swarm Optimization (PSO).
  The models generated include Finite Impulse Response (FIR), Nonlinear Finite Impulse Response (NFIR),
  AutoRegressive with eXogenous inputs (ARX), and Nonlinear AutoRegressive with eXogenous inputs (NARX).
  These models can be both univariate and multivariate. Additionally, the package
  incorporates a scoring filter to evaluate the quality of the autoregulation response,
  particularly when the patient is subjected to simulated pressure changes.
License: MIT + file LICENSE
RoxygenNote: 7.2.3
Encoding: UTF-8
Imports: 
    dplyr,
    signal,
    stats,
    e1071,
    utils,
    pso,
    progress,
    magrittr
Suggests: 
    testthat