4 projects for "data quality cleansing" with 2 filters applied:

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  • 1
    Criterial

    Criterial

    The package for statistical data analysis and applied mathematics

    Putting truth before show-off. Criterial is an add-in for desktop versions of LibreOffice Calc (and forks) for statistical data analysis. The project is built on the refined expertise and core concepts of the AtteStat and StatAnt projects. Completely free. No donations required. Comes with absolutely no warranty. Rating: Everyone (All ages). MEDICAL DISCLAIMER: This software is not certified for use in healthcare and should not be used for diagnostic or treatment purposes. NOTICE FOR EU...
    Downloads: 2 This Week
    Last Update:
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  • 2
    A Matlab software routine to perform Principal Component Analysis using Covariance, Correlation or Comedian as the criterion. Though, initially developed for experiments related to fretting wear but can be effectively used to interpret experimental data from any field. The attached files contain source code as well as a sample MATLAB (.mat) data file of 13 variables. It could be replaced to the data file of your choice. The code is open source but you are requested to give credits if used. Additionally, it also has some useful functions for exporting and generating publication quality figures for different kind of figures in MATLAB
    Downloads: 0 This Week
    Last Update:
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  • 3

    Weibull-based reliability toolkit for R

    R package for Weibull analysis on (life-)time observations.

    This is a small R package for doing Weibull-based reliability analysis. This R package is now obsolete and has been superseded by 'project Abernethy' on http://r-forge.r-project.org/projects/abernethy/.
    Downloads: 0 This Week
    Last Update:
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  • 4
    A MATLAB package to simulate sample paths of the solution of a Itô or Stratonovich stochastic differential equation (SDE), compute statistics and estimate the parameters from data. A note of caution: SDE Toolbox is no more developed but it's still downloadable. Its inferential capabilities can be considered surpassed (at best). Actually the parameter estimation methods were already far from the state-of-art when the project began in 2007 (!). The considered implemented parametric and non-parametric Monte Carlo likelihood methods were chosen for their ability to treat both one-dimensional and multivariate SDE systems, although the quality of the inferential results can't match those obtained using more advanced techniques. ...
    Downloads: 0 This Week
    Last Update:
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