Description: GMD is a package for non-parametric distance measurement between
Collate: 'GMD-package.R' 'imports.R' 'util.R' 'GMD-internal.R'
'GMD-data.R' 'ghist.R' 'gdist.R' 'css.R' 'heatmap3.R' 'gmdp.R'

Author: Xiaobei Zhao <xiaobei@binf.ku.dk>, Albin Sandelin <albin@binf.ku.dk>
Description: GMD is a package for non-parametric distance measurement between two discrete frequency distributions.

Title: Predicting and Forecasting Time Series via GMDH-Type Neural
Description: Group method of data handling (GMDH) - type neural network algorithm is the heuristic self-organization method for modelling the complex systems. In this package, GMDH-type neural network algorithms are applied to predict and forecast a univariate time series.

Title: Short Term Forecasting via GMDH-Type Neural Network Algorithms
Description: Group method of data handling (GMDH) - type neural network algorithm is the heuristic self-organization method for modelling the complex systems. In this package, GMDH-type neural network algorithms are applied to make short term forecasting for a univariate time series.

Title: Binary Classification via GMDH-Type Neural Network Algorithm
Imports: e1071, utils, graphics, stats, randomForest, glmnet, nnet,
Author: Osman Dag [aut, cre], Erdem Karabulut [aut], Reha Alpar [aut]
Description: Performs binary classification via Group Method of Data Handling (GMDH) - type neural network algorithm. Also, it produces a well-formatted table of descriptives for a binary response. Moreover, it returns confusion matrix and related statistics and scatter plot with classification labels of binary classes to assess the prediction performance. All 'GMDH2' functions are designed for a binary response. See Dag O. and Yozgatligil C. (2016, ISSN:2073-4859) and Kondo T. and Ueno J. (2016, ISSN:1349-4198) for the details of GMDH algorithms.

Description: Performs binary classification via Group Method of Data Handling (GMDH) - type neural network algorithm. There exist two main algorithms available in GMDH() and dceGMDH() functions. GMDH() performs classification via GMDH algorithm for a binary response and returns important variables. dceGMDH() performs classification via diverse classifiers ensemble based on GMDH (dce-GMDH) algorithm. Also, the package produces a well-formatted table of descriptives for a binary response. Moreover, it produces confusion matrix and related statistics and scatter plot (2D and 3D) with classification labels of binary classes to assess the prediction performance. All 'GMDH2' functions are designed for a binary response. See Dag O. and Yozgatligil C. (2016, ISSN:2073-4859) and Kondo T. and Ueno J. (2016, ISSN:1349-4198) for the details of GMDH algorithms.