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Tools to Analyse RFLP Data
Provides functions to analyse DNA fragment samples (i.e. derived from RFLP-analysis) and standalone BLAST report files (i.e. DNA sequence analysis).
Fit and Deploy DECORATE Trees
DECORATE (Diverse Ensemble Creation by Oppositional Relabeling
of Artificial Training Examples) builds an ensemble of J48 trees by recursively
adding artificial samples of the training data ("Melville, P., & Mooney, R. J. (2005)
Quantile-Quantile Plot with Several Gaussian Simulations
Plots a QQ-Norm Plot with several Gaussian simulations.
Create Waffle Chart Visualizations
Square pie charts (a.k.a. waffle charts) can be used to communicate parts of a whole for categorical quantities. To emulate the percentage view of a pie chart, a 10x10 grid should be used with each square representing 1% of the total. Modern uses of waffle charts do not necessarily adhere to this rule and can be created with a grid of any rectangular shape. Best practices suggest keeping the number of categories small, just as should be done when creating pie charts. Tools are provided to create waffle charts as well as stitch them together, and to use glyphs for making isotype pictograms.
Draw Samples of Truncated Multivariate Normal Distributions
Draw samples from truncated multivariate normal distribution using the sequential nearest neighbor (SNN) method introduced in "Scalable Sampling of Truncated Multivariate Normals Using Sequential Nearest-Neighbor Approximation"
Closed Testing Procedure (CTP)
This is a package for constructing hypothesis trees for treatment comparisons based
on the closure principle and analysing the corresponding Closed Testing Procedures (CTP)
using adjusted p-values. For reference, see
Marcus, R., Peritz, E, and Gabriel, K.R. (1976)
Taxonomic Information from Around the Web
Interacts with a suite of web application programming interfaces (API) for taxonomic tasks, such as getting database specific taxonomic identifiers, verifying species names, getting taxonomic hierarchies, fetching downstream and upstream taxonomic names, getting taxonomic synonyms, converting scientific to common names and vice versa, and more. Some of the services supported include 'NCBI E-utilities' (< https://www.ncbi.nlm.nih.gov/books/NBK25501/>), 'Encyclopedia of Life' (< https://eol.org/docs/what-is-eol/data-services>), 'Global Biodiversity Information Facility' (< https://techdocs.gbif.org/en/openapi/>), and many more. Links to the API documentation for other supported services are available in the documentation for their respective functions in this package.
Boosting Methods for 'GAMLSS'
Boosting models for fitting generalized additive models for location, shape and scale ('GAMLSS') to potentially high dimensional data.
'Google Ads API' Interface
Interface for the 'Google Ads API'. 'Google Ads' is an online advertising service that enables advertisers to display advertising to web users (see < https://developers.google.com/google-ads/> for more information).
Linear and Smooth Predictor Modelling with Penalisation and Variable Selection
Fit a model with potentially many linear and smooth predictors. Interaction effects can also be quantified. Variable selection is done using penalisation. For l1-type penalties we use iterative steps alternating between using linear predictors (lasso) and smooth predictors (generalised additive model).