Showing 4 open source projects for "statistical process control"

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  • 1
    AtteStat

    AtteStat

    The package for statistical data analysis and applied mathematics

    Less means - more power. AtteStat is an add-in for desktop versions of the Microsoft Excel. Winner of contest Microsoft Office Extensions (PC Magazine RE) in 2006. Registered 2002-05-23 with the Federal Service for Intellectual Property. 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: 13 This Week
    Last Update:
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  • 2
    fcGENE: Genotype  format converter

    fcGENE: Genotype format converter

    Format converting tool for genotype Data (e.g.PLINK-MACH,MACH-PLINK)

    Main application is twofold: first to convert genotype SNP data into formats of different imputation tools like PLINK MACH, IMPUTE, BEAGLE and BIMBBAM, second to transform imputed data into different file formats like PLINK, HAPLOVIEW, EIGENSOFT and SNPTEST. Readable file formats: plink-pedigree (ped and map), plink-raw, plink-dosage, mach , minimac, impute, snptest, beagle and bimbam. Similarly all kinds of imputation of outputs are also accepted. Formats which can be generated by...
    Downloads: 9 This Week
    Last Update:
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  • 3

    Excelsi-R

    Excel's Interface to R

    Excelsi-R is an Excel add-in that allows Excel spreadsheets to harness the power of the R statistical language by connecting to a running R process. R does not need to be installed on the computer running Excel, but it does require access to an R instance running Rserve (which can be on a remote computer). It supports incorporating R plots and graphs in an Excel workbook.
    Downloads: 0 This Week
    Last Update:
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  • 4
    phcfM

    phcfM

    R package for modelling anthropogenic deforestation

    ...It was named after the REDD+ pilot-project 'programme holistique de conservation des forêts à Madagascar'. phcfM includes two main functions: (i) demography(), to model the population growth with time in a hierarchical Bayesian framework using population census data and Gaussian linear mixed models and (ii) deforestation(), to model the deforestation process in a hierarchical Bayesian framework using land-cover change data and Binomial logistic regression models with variable time-intervals between land-cover observations. The two functions use embedded Gibbs samplers written in C++ with the Scythe statistical library to reduce computational time.
    Downloads: 0 This Week
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