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Select Variables for Optimal Clustering
Finding hidden clusters in structured data can be hindered
by the presence of masking variables. If not detected,
masking variables are used to calculate the overall similarities between units,
and therefore the cluster attribution is more imprecise.
The algorithm q-vars implements an optimization method to find the variables
that most separate units between clusters. In this way, masking variables can be
discarded from the data frame and the clustering is more accurate.
Tests can be found in Benati et al.(2017)
A Naive IPA Tokeniser
It provides users with functions to parse International Phonetic Alphabet (IPA) transcriptions into individual phones (tokenisation) based on default IPA symbols and optional user specified multi-character phones. The tokenised transcriptions can be used for obtaining counts of phones or for searching for words matching phonetic patterns.
Conversion of Nuclear Magnetic Resonance Spectra in Audio Files
A collection of functions for converting and visualization the free induction decay of mono dimensional nuclear magnetic resonance (NMR) spectra into an audio file. It facilitates the conversion of Bruker datasets in files WAV. The sound of NMR signals could provide an alternative to the current representation of the individual metabolic fingerprint and supply equally significant information. The package includes also NMR spectra of the urine samples provided by four healthy donors. Based on Cacciatore S, Saccenti E, Piccioli M. Hypothesis: the sound of the individual metabolic phenotype? Acoustic detection of NMR experiments. OMICS. 2015;19(3):147-56.
A Wrapper for the Phonetic Software 'Praat'
It allows running 'Praat' scripts from R and it provides some wrappers for basic plotting. It also adds support for literate markdown tangling. The package is designed to bring reproducible phonetic research into R.
Simulation-Based Inference for Regression Models
Performs simulation-based inference as an alternative to the delta method for obtaining valid confidence intervals and p-values for regression post-estimation quantities, such as average marginal effects and predictions at representative values. This framework for simulation-based inference is especially useful when the resulting quantity is not normally distributed and the delta method approximation fails. The methodology is described in King, Tomz, and Wittenberg (2000)
Compute and Display Tendril Plots
Compute the coordinates to produce a tendril plot.
In the tendril plot, each tendril (branch) represents a type of events,
and the direction of the tendril is dictated by on which treatment arm the
event is occurring. If an event is occurring on the first of the two
specified treatment arms, the tendril bends in a clockwise direction.
If an event is occurring on the second of the treatment arms, the
tendril bends in an anti-clockwise direction.
Ref: Karpefors, M and Weatherall, J., "The Tendril Plot - a novel visual summary
of the incidence, significance and temporal aspects of adverse events in
clinical trials" - JAMIA 2018; 25(8): 1069-1073
Social Ranking Solutions for Power Relations on Coalitions
The notion of power index has been widely used in literature to evaluate the influence of individual players (e.g., voters, political parties, nations, stockholders, etc.) involved in a collective decision situation like an electoral system, a parliament, a council, a management board, etc., where players may form coalitions. Traditionally this ranking is determined through numerical evaluation. More often than not however only ordinal data between coalitions is known. The package 'socialranking' offers a set of solutions to rank players based on a transitive ranking between coalitions, including through CP-Majority, ordinal Banzhaf or lexicographic excellence solution summarized by Tahar Allouche, Bruno Escoffier, Stefano Moretti and Meltem Öztürk (2020,
Interactively Gate Points
Interactively gate points on a scatter plot. Interactively drawn gates are recorded and can be applied programmatically to reproduce results exactly. Programmatic gating is based on the package gatepoints by Wajid Jawaid (who is also an author of this package).
Knowledge Discovery by Accuracy Maximization
An unsupervised and semi-supervised learning algorithm that performs feature extraction
from noisy and high-dimensional data. It facilitates identification of patterns representing underlying
groups on all samples in a data set. Based on Cacciatore S, Tenori L, Luchinat C, Bennett PR, MacIntyre DA.
(2017) Bioinformatics
Tidy Model Visualisation for Generalised Additive Models
Provides functions for visualising generalised additive models and getting predicted values using tidy tools from the 'tidyverse' packages.