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Epimed Solutions Collection for Data Editing, Analysis, and Benchmark of Health Units
Collection of functions related to benchmark with prediction models for data analysis and editing of clinical and epidemiological data.
Stability-enHanced Approaches using Resampling Procedures
In stability selection (N Meinshausen, P Bühlmann (2010)
Flexible Data Simulation Using the Multivariate Normal Distribution
This R package can be used to generate artificial data conditionally on pre-specified (simulated or user-defined) relationships between the variables and/or observations. Each observation is drawn from a multivariate Normal distribution where the mean vector and covariance matrix reflect the desired relationships. Outputs can be used to evaluate the performances of variable selection, graphical modelling, or clustering approaches by comparing the true and estimated structures (B Bodinier et al (2021)
Datasets for Agresti and Finlay's "Statistical Methods for the Social Sciences"
Datasets used in "Statistical Methods for the Social Sciences" (SMSS) by Alan Agresti and Barbara Finlay.
Load Test Shiny Applications
Assesses the number of concurrent users 'shiny' applications are capable of supporting, and for directing application changes in order to support a higher number of users. Provides facilities for recording 'shiny' application sessions, playing recorded sessions against a target server at load, and analyzing the resulting metrics.
Tool Kit to Implement a W.A.S.P.A.S. Based Multi-Criteria Decision Analysis Solution
Provides a set of functions to implement decision-making systems
based on the W.A.S.P.A.S. method (Weighted Aggregated Sum Product Assessment),
Chakraborty and Zavadskas (2012)
Provenance Visualizer
Displays provenance graphically for provenance collected by the 'rdt' or
'rdtLite' packages, or other tools providing compatible PROV JSON output. The exact
format of the JSON created by 'rdt' and 'rdtLite' is described in
< https://github.com/End-to-end-provenance/ExtendedProvJson>. More information about
rdtLite and associated tools is available at < https://github.com/End-to-end-provenance/>
and Barbara Lerner, Emery Boose, and Luis Perez (2018), Using Introspection to Collect
Provenance in R, Informatics,
Network Analysis and Causal Inference Through Structural Equation Modeling
Estimate networks and causal relationships in complex systems through
Structural Equation Modeling. This package also includes functions to import,
weight, manipulate, and fit biological network models within the
Structural Equation Modeling framework proposed in
Grassi M, Palluzzi F, Tarantino B (2022)
Creates Adjacency Matrices for Lineage Searches
Creates and manages a provenance graph corresponding to the provenance created by the 'rdtLite' package, which collects provenance from R scripts. 'rdtLite' is available on CRAN. The provenance format is an extension of the W3C PROV JSON format (< https://www.w3.org/Submission/2013/SUBM-prov-json-20130424/>). The extended JSON provenance format is described in < https://github.com/End-to-end-provenance/ExtendedProvJson>.
Discovery of Motifs in Spatial-Time Series
Allow to identify motifs in spatial-time series. A motif is a previously unknown subsequence of a (spatial) time series with relevant number of occurrences. For this purpose, the Combined Series Approach (CSA) is used.