Department of Biostatistics - SoftMed Research Group


Statistical Computing - Machine Learning Algorithms - Decision Support Systems - GMDH-Type Neural Network Algorithms - Data Transformations - Time Series Analysis

TOOLS


About


SoftMed Research Group is composed to develop free web applications for medical research using the R language environment. The project is started in 2018 at Hacettepe University Department of Biostatistics and it is managed by Department of Biostatistics.

PUBLICATIONS


  • Dag, O., Dolgun, A., Konar, N.M. (2018). onewaytests: An R Package for One-Way Tests in Independent Groups Designs. The R Journal, 10:1, 175-199.
  • Dag, O., Ilk, O. (2017). An Algorithm for Estimating Box-Cox Transformation Parameter in ANOVA. Communications in Statistics - Simulation and Computation, 46:8, 6424-6435.
  • Asar, O., Ilk, O., Dag, O. (2017). Estimating Box-Cox Power Transformation Parameter Via Goodness-of-Fit Tests. Communications in Statistics - Simulation and Computation, 46:1, 91-105.
  • Dag, O., Yozgatligil, C. (2016). GMDH: An R Package for Short Term Forecasting Via GMDH-Type Neural Network Algorithms. The R Journal, 8:1, 379-386.
  • Dag, O., Asar, O., Ilk, O. (2014). A Methodology to Implement Box-Cox Transformation When No Covariate is Available. Communications in Statistics - Simulation and Computation, 43:7, 1740-1759.
  • R PACKAGES


  • Dag, O., Karabulut, E., Alpar, R. GMDH2: Binary Classification via GMDH-Type Neural Network Algorithms.
  • Dag, O., Dolgun, A., Konar, N.M. onewaytests: One-Way Tests in Independent Groups Designs.
  • Dag, O., Yozgatligil, C. GMDH: Short Term Forecasting via GMDH-Type Neural Network Algorithms.
  • Dag, O., Asar, O., Ilk, O. AID: Box-Cox Power Transformation.
  • Onewaytests


    Performs one-way tests in independent groups designs, pairwise comparisons, graphical approaches, assesses variance homogeneity and normality of data in each group via tests and plots.

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    GMDH2


    This web-tool enables the researchers to performs binary classification via GMDH-type neural network algorithms. There exist two main algorithms, GMDH algorithm and diverse classifiers ensemble based on GMDH (dce-GMDH) algorithm. GMDH algorithm performs classification for a binary response and returns important variables dominating the system. dce-GMDH algorithm performs binary classification by assembling classifiers based on GMDH algorithm.

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