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Mark-Recapture Analysis for Survival and Abundance Estimation
Functions for fitting various models to capture-recapture data including mixed-effects Cormack-Jolly-Seber(CJS) and multistate models and the multi-variate state model structure for survival estimation and POPAN structured Jolly-Seber models for abundance estimation. There are also Hidden Markov model (HMM) implementations of CJS and multistate models with and without state uncertainty and a simulation capability for HMM models.
Import 'OpenStreetMap' Data as Simple Features or Spatial Objects
Download and import of 'OpenStreetMap' ('OSM') data as 'sf' or 'sp' objects. 'OSM' data are extracted from the 'Overpass' web server and processed with very fast 'C++' routines for return to 'R'.
Fit, Simulate and Diagnose Exponential-Family Models for Networks
An integrated set of tools to analyze and simulate networks based on exponential-family random graph models (ERGMs). 'ergm' is a part of the Statnet suite of packages for network analysis.
Extrema-Weighted Feature Extraction
Extrema-weighted feature extraction for varying length functional data. Functional data analysis method that performs dimensionality reduction based on predefined features and allows for quantile weighting. Method implemented as presented in Van den Boom et al. (2018)
C5.0 Decision Trees and Rule-Based Models
C5.0 decision trees and rule-based models for pattern recognition that extend the work of Quinlan (1993, ISBN:1-55860-238-0).
USA Presidential Elections Data
This includes a dataset on the outcomes of the USA presidential elections since 1920, and various predictors, as used in < http://vanderwalresearch.com/blog/15-elections>.
Compositional Data Analysis
Provides functions for the consistent analysis of compositional data (e.g. portions of substances) and positive numbers (e.g. concentrations) in the way proposed by J. Aitchison and V. Pawlowsky-Glahn.
Quality Control of Genome Wide Association Study results
Tools for (automated and manual) quality control of the results of Genome Wide Association Studies
A Genetic Algorithm for Fixed-Size Subset Selection
Provides a function that uses a genetic algorithm to search for a subset of size k from the integers 1:n, such that a user-supplied objective function is minimized at that subset. The selection step is done by tournament selection based on ranks, and elitism may be used to retain a portion of the best solutions from one generation to the next. Population objective function values may optionally be evaluated in parallel.