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Interface for MOA Stream Clustering Algorithms
Interface for data stream clustering algorithms implemented in the MOA (Massive Online Analysis) framework (Albert Bifet, Geoff Holmes, Richard Kirkby, Bernhard Pfahringer (2010). MOA: Massive Online Analysis, Journal of Machine Learning Research 11: 1601-1604).
Open Perimetry Interface
Implementation of the Open Perimetry Interface (OPI) for simulating and controlling visual field machines using R. The OPI is a standard for interfacing with visual field testing machines (perimeters) first started as an open source project with support of Haag-Streit in 2010. It specifies basic functions that allow many visual field tests to be constructed. As of February 2022 it is fully implemented on the Haag-Streit Octopus 900 with partial implementations on the Centervue Compass, Kowa AP 7000, Android phones and the CrewT IMO. It also has a cousin: the R package 'visualFields', which has tools for analysing and manipulating visual field data.
Scalable Gaussian-Process Approximations
Fast scalable Gaussian process approximations, particularly well suited to spatial (aerial, remote-sensed) and environmental data, described in more detail in Katzfuss and Guinness (2017)
Extensions of Package 'distr' for Teaching Stochastics/Statistics in Secondary School
Provides flexible examples of LLN and CLT for teaching purposes in secondary school.
Nonparametric Analysis of Longitudinal Data in Factorial Experiments
Performs nonparametric analysis of longitudinal data in factorial experiments. Longitudinal data are those which are collected from the same subjects over time, and they frequently arise in biological sciences. Nonparametric methods do not require distributional assumptions, and are applicable to a variety of data types (continuous, discrete, purely ordinal, and dichotomous). Such methods are also robust with respect to outliers and for small sample sizes.
Documentation for 'distr' Family of R Packages
Provides documentation in form of a common vignette to packages 'distr', 'distrEx', 'distrMod', 'distrSim', 'distrTEst', 'distrTeach', and 'distrEllipse'.
Shiny Apps for Lateral Flow Assays
Shiny apps for the quantitative analysis of images from lateral flow assays (LFAs). The images are segmented and background corrected and color intensities are extracted. The apps can be used to import and export intensity data and to calibrate LFAs by means of linear, loess, or gam models. The calibration models can further be saved and applied to intensity data from new images for determining concentrations.
Interface to OpenSubspace
An interface to 'OpenSubspace', an open source framework for evaluation and exploration of subspace clustering algorithms in WEKA (see < http://dme.rwth-aachen.de/de/opensubspace> for more information). Also performs visualization.
Fitting, Comparing, and Visualizing Networks Based on Time Series Data
Fit, compare, and visualize Bayesian graphical vector autoregressive (GVAR) network models using 'Stan'. These models are commonly used in psychology to represent temporal and contemporaneous relationships between multiple variables in intensive longitudinal data. Fitted models can be compared with a test based on matrix norm differences of posterior point estimates to quantify the differences between two estimated networks. See also Siepe, Kloft & Heck (2024)
Trace Plots, Density Plots and Chain Comparisons for MCMC Samples
Provides methods for examining posterior MCMC samples
from a single chain using trace plots and density plots, and from
multiple chains by comparing posterior medians and credible intervals
from each chain. These plotting functions have a variety of options,
such as figure sizes, legends, parameters to plot, and saving plots to file.
Functions interface with the NIMBLE software package, see
de Valpine, Turek, Paciorek, Anderson-Bergman, Temple Lang and Bodik (2017)