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mhahsler

stream:Infrastructure for Data Stream Mining

A framework for data stream modeling and associated data mining tasks such as clustering and classification. The development of this package was supported in part by NSF IIS-0948893, NSF CMMI 1728612, and NIH R21HG005912. Hahsler et al (2017) <doi:10.18637/jss.v076.i14>.

Maintained by Michael Hahsler. Last updated 21 days ago.

data-stream-clusteringdatastreamstream-miningcpp

39 stars 10.05 score 132 scripts 3 dependents

bioc

funtooNorm:Normalization Procedure for Infinium HumanMethylation450 BeadChip Kit

Provides a function to normalize Illumina Infinium Human Methylation 450 BeadChip (Illumina 450K), correcting for tissue and/or cell type.

Maintained by Kathleen Klein. Last updated 5 months ago.

dnamethylationpreprocessingnormalization

3.70 score

r-forge

agrmt:Calculate Concentration and Dispersion in Ordered Rating Scales

Calculates concentration and dispersion in ordered rating scales. It implements various measures of concentration and dispersion to describe what researchers variably call agreement, concentration, consensus, dispersion, or polarization among respondents in ordered data. It also implements other related measures to classify distributions. In addition to a generic city-block based concentration measure and a generic dispersion measure, the package implements various measures, including van der Eijk's (2001) <DOI: 10.1023/A:1010374114305> measure of agreement A, measures of concentration by Leik, Tatsle and Wierman, Blair and Lacy, Kvalseth, Berry and Mielke, Reardon, and Garcia-Montalvo and Reynal-Querol. Furthermore, the package provides an implementation of Galtungs AJUS-system to classify distributions, as well as a function to identify the position of multiple modes.

Maintained by Didier Ruedin. Last updated 2 months ago.

3.58 score 38 scripts

cran

papci:Prevalence Adjusted PPV Confidence Interval

Positive predictive value (PPV) defined as the conditional probability of clinical trial assay (CTA) being positive given Companion diagnostic device (CDx) being positive is a key performance parameter for evaluating the clinical validity utility of a companion diagnostic test in clinical bridging studies. When bridging study patients are enrolled based on CTA assay results, Binomial-based confidence intervals (CI) may are not appropriate for PPV CI estimation. Bootstrap CIs which are not restricted by the Binomial assumption may be used for PPV CI estimation only when PPV is not 100%. Bootstrap CI is not valid when PPV is 100% and becomes a single value of [1, 1]. We proposed a risk ratio-based method for constructing CI for PPV. By simulation we illustrated that the coverage probability of the proposed CI is close to the nominal value even when PPV is high and negative percent agreement (NPA) is close to 100%. There is a lack of R package for PPV CI calculation. we developed a publicly available R package along with this shiny app to implement the proposed approach and some other existing methods.

Maintained by Cui Guo. Last updated 4 years ago.

1 stars 1.00 score

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