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R Package for Fitting the Multinomial Probit Model
Fits the Bayesian multinomial probit model via Markov chain
Monte Carlo. The multinomial probit model is often used to analyze
the discrete choices made by individuals recorded in survey data.
Examples where the multinomial probit model may be useful include the
analysis of product choice by consumers in market research and the
analysis of candidate or party choice by voters in electoral studies.
The MNP package can also fit the model with different choice sets for
each individual, and complete or partial individual choice orderings
of the available alternatives from the choice set. The estimation is
based on the efficient marginal data augmentation algorithm that is
developed by Imai and van Dyk (2005). ``A Bayesian Analysis of the
Multinomial Probit Model Using the Data Augmentation,'' Journal of
Econometrics, Vol. 124, No. 2 (February), pp. 311-334.
Relative Risk Regression Using the Log-Binomial Model
Methods for fitting log-link GLMs and GAMs to binomial data, including EM-type algorithms with more stable convergence properties than standard methods.
Helper Functions for Rmd Documents
A series of functions to aid in repeated tasks for Rmd documents. All details are to my personal preference, though I am happy to add flexibility if there are use cases I am missing. I will continue updating with new functions as I add utility functions for myself.
Conditional Visualization for Statistical Models
Exploring fitted models by interactively taking 2-D and 3-D sections in data space.
Advanced Tensor Arithmetic with Named Indices
Provides convenience functions for advanced linear algebra with tensors and computation with datasets of tensors on a higher level abstraction. It includes Einstein and Riemann summing conventions, dragging, co- and contravariate indices, parallel computations on sequences of tensors.
Fast and Easy Quality Control of EWAS Results Files
Tools for (automated and manual) quality control of the results of Epigenome-Wide Association Studies.
Core Methods and Classes Used by 'aroma.*' Packages Part of the Aroma Framework
Core methods and classes used by higher-level 'aroma.*' packages part of the Aroma Project, e.g. 'aroma.affymetrix' and 'aroma.cn'.
Tools rewritten in C for various smoothing tasks
Tools to Analyze Repertory Grid Data
Analyze repertory grids, a qualitative-quantitative
data collection technique devised by George A. Kelly in the 1950s. Today, grids are used across
various domains ranging from clinical psychology to marketing. The package contains
functions to quantitatively analyze and visualize repertory grid data
(see e.g. Bell, 2005,
Detection of Fixations in Eye-Tracking Data
Functions for detecting eye fixations in raw eye-tracking data. The detection is done using a velocity-based algorithm for saccade detection proposed by Ralf Engbert and Reinhold Kliegl in 2003. The algorithm labels segments as saccades when the velocity of the eye movement exceeds a certain threshold. Anything between two saccades is considered a fixation. Thus the algorithm is not appropriate for data containing episodes of smooth pursuit eye movements.