Twitter Conversation Networks and Analysis

Collects tweets and metadata for threaded conversations and generates networks.

Interactive Exploration of Contour Data

Interactive tools to explore topographic-like data sets. Such data sets take the form of a matrix in which the rows and columns provide location/frequency information, and the matrix elements contain altitude/response information. Such data is found in cartography, 2D spectroscopy and chemometrics. The functions in this package create interactive web pages showing the contoured data, possibly with slices from the original matrix parallel to each dimension. The interactive behavior is created using the 'D3.js' 'JavaScript' library by Mike Bostock.

Finding Rhythms Using Extended Circadian Harmonic Oscillators (ECHO)

Provides a function (echo_find()) designed to find rhythms from data using extended harmonic oscillators. For more information, see H. De los Santos et al. (2020) .

Missing Data Imputation and Model Checking

The mi package provides functions for data manipulation, imputing missing values in an approximate Bayesian framework, diagnostics of the models used to generate the imputations, confidence-building mechanisms to validate some of the assumptions of the imputation algorithm, and functions to analyze multiply imputed data sets with the appropriate degree of sampling uncertainty.

Run Code 'With' Temporarily Modified Global State

A set of functions to run code 'with' safely and temporarily modified global state. Many of these functions were originally a part of the 'devtools' package, this provides a simple package with limited dependencies to provide access to these functions.

Compact and Flexible Summaries of Data

A simple to use summary function that can be used with pipes and displays nicely in the console. The default summary statistics may be modified by the user as can the default formatting. Support for data frames and vectors is included, and users can implement their own skim methods for specific object types as described in a vignette. Default summaries include support for inline spark graphs. Instructions for managing these on specific operating systems are given in the "Using skimr" vignette and the README.

Collecting Social Media Data and Generating Networks for Analysis

A suite of easy to use functions for collecting social media data and generating networks for analysis. Supports Twitter, YouTube, Reddit and web site data sources.

Modelling of Extreme Values

Various tools for the analysis of univariate, multivariate and functional extremes. Exact simulation from max-stable processes [Dombry, Engelke and Oesting (2016) , R-Pareto processes for various parametric models, including Brown-Resnick (Wadsworth and Tawn, 2014, ) and Extremal Student (Thibaud and Opitz, 2015, ). Threshold selection methods, including Wadsworth (2016) , and Northrop and Coleman (2014) . Multivariate extreme diagnostics. Estimation and likelihoods for univariate extremes, e.g., Coles (2001) .

Penalised Maximum Likelihood Estimation for Hidden Semi-Markov Models

Provides tools for penalised maximum likelihood estimation of hidden semi-Markov models (HSMMs) with flexible state dwell-time distributions. These include functions for model fitting, model checking and state-decoding. The package considers HSMMs for univariate time series with state-dependent gamma, normal, Poisson or Bernoulli distributions. For details, see Pohle, J., Adam, T. and Beumer, L.T. (2021): Flexible estimation of the state dwell-time distribution in hidden semi-Markov models. .

'BLAS' and 'LAPACK' Routines for Native R Matrices and 'big.matrix' Objects

Provides arithmetic functions for R matrix and 'big.matrix' objects as well as functions for QR factorization, Cholesky factorization, General eigenvalue, and Singular value decomposition (SVD). A method matrix multiplication and an arithmetic method -for matrix addition, matrix difference- allows for mixed type operation -a matrix class object and a big.matrix class object- and pure type operation for two big.matrix class objects.