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) .

Regression Data Analysis System

Perform a supervised data analysis on a database through a 'shiny' graphical interface. It includes methods such as linear regression, penalized regression, k-nearest neighbors, decision trees, ada boosting, extreme gradient boosting, random forest, neural networks, deep learning and support vector machines.

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.

Create Common TLGs Used in Clinical Trials

Table, Listings, and Graphs (TLG) library for common outputs used in clinical trials.

Rank Intraclass Correlation for Clustered Data

Estimates the rank intraclass correlation coefficient (ICC) for clustered continuous and ordinal data. See Tu et al. (2023) for details.

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 Mastodon, YouTube, Reddit and Web 1.0 data sources.

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. .

Multivariate VAM Fitting

Fits a multivariate value-added model (VAM), see Broatch, Green, and Karl (2018) and Broatch and Lohr (2012) , with normally distributed test scores and a binary outcome indicator. A pseudo-likelihood approach, Wolfinger (1993) , is used for the estimation of this joint generalized linear mixed model. The inner loop of the pseudo-likelihood routine (estimation of a linear mixed model) occurs in the framework of the EM algorithm presented by Karl, Yang, and Lohr (2013) . This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.