close

Showing 4 of total 4 results (show query)

mariarizzo

energy:E-Statistics: Multivariate Inference via the Energy of Data

E-statistics (energy) tests and statistics for multivariate and univariate inference, including distance correlation, one-sample, two-sample, and multi-sample tests for comparing multivariate distributions, are implemented. Measuring and testing multivariate independence based on distance correlation, partial distance correlation, multivariate goodness-of-fit tests, k-groups and hierarchical clustering based on energy distance, testing for multivariate normality, distance components (disco) for non-parametric analysis of structured data, and other energy statistics/methods are implemented.

Maintained by Maria Rizzo. Last updated 7 months ago.

distance-correlationenergymultivariate-analysisstatisticscpp

45 stars 10.69 score 634 scripts 45 dependents

rpatin

segclust2d:Bivariate Segmentation/Clustering Methods and Tools

Provides two methods for segmentation and joint segmentation/clustering of bivariate time-series. Originally intended for ecological segmentation (home-range and behavioural modes) but easily applied on other series, the package also provides tools for analysing outputs from R packages 'moveHMM' and 'marcher'. The segmentation method is a bivariate extension of Lavielle's method available in 'adehabitatLT' (Lavielle, 1999 <doi:10.1016/S0304-4149(99)00023-X> and 2005 <doi:10.1016/j.sigpro.2005.01.012>). This method rely on dynamic programming for efficient segmentation. The segmentation/clustering method alternates steps of dynamic programming with an Expectation-Maximization algorithm. This is an extension of Picard et al (2007) <doi:10.1111/j.1541-0420.2006.00729.x> method (formerly available in 'cghseg' package) to the bivariate case. The method is fully described in Patin et al (2018) <doi:10.1101/444794>.

Maintained by Remi Patin. Last updated 11 months ago.

cpp

7 stars 5.98 score 30 scripts 1 dependents

heorlytics

closeloop:Integrate Single-Arm Observational Data in Network Meta Analysis

This package Calculates distance between single-arm observational studies by using co-variates information to remove heterogeneity in Network Meta-Analysis in Randomized clinical trials. This package will facilitate the inclusion of observational data in Network Meta ANalysis, thereby enhancing the comprehensiveness and robustness of comparative effectiveness research.The proposed R package will provide researchers with a powerful tool to systematically adjust for heterogeneity in single-arm observational studies, enabling their integration into NMAs. This will improve the accuracy and reliability of comparative effectiveness research, ultimately informing better healthcare decisions. Schmitz S et. al. The use of single armed observational data to closing the gap in otherwise disconnected evidence networks: a network meta-analysis in multiple myeloma. BMC Med Res Methodol. 2018 Jun 28;18(1):66. doi: 10.1186/s12874-018-0509-7. PMID: 29954322; PMCID: PMC6022299.

Maintained by Shubhram Pandey. Last updated 9 months ago.

3.00 score

paithiov909

apportita:Utility for Handling 'magnitude' Word Embeddings

A partial R port from 'magnitude', which is a fast, simple utility library for handling vector embeddings. The main goal of this package is to enable access to user's local magnitude data store.

Maintained by Akiru Kato. Last updated 2 months ago.

embeddings

1 stars 1.70 score 4 scripts

: