Paul-Christian Bürkner (paul-buerkner)

paul-buerkner

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Location:Department of Statistics, TU Dortmund University

Home Page:https://paul-buerkner.github.io/

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Paul-Christian Bürkner's repositories

brms

brms R package for Bayesian generalized multivariate non-linear multilevel models using Stan

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Bayesian-IRT-paper

This repository contains all materials for the paper "Bayesian Item Response Modelling in R Using brms and Stan" by Paul Bürkner.

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thurstonianIRT

Fit Thurstonian IRT models in R using Stan, lavaan, or Mplus

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custom-brms-families

R scripts for custom brms families

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monotonic-effects-paper

This repository contains a manuscript in which we introduce monotonic effects.

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psis-non-factorized-paper

The repository contains all the materials related to the paper "Efficient leave-one-out cross-validation for Bayesian non-factorized normal and Student-t models".

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paul-buerkner.github.io

Website of Paul Bürkner

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SPM-IRT-models

This repository contains all materials for the paper "Analysing Standard Progressive Matrics (SPM-LS) with Bayesian Item Response Models" by Paul Bürkner and Marie Beisemann.

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bayesnec

Bayesian No-Effect-Concentration estimation in R

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non-factorized-loo

LOO for non-factorizable normal models

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bayes-workflow-book

Source files for the book "Bayesian Workflow Using Stan"

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brms-multilevel-paper

This repository contains reproduction material for the paper "Advanced Bayesian Multilevel Modeling with the R Package brms" by Paul-Christian Bürkner as published in the R Journal.

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ggplot2

An implementation of the Grammar of Graphics in R

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m-step-ahead-predictions

m-step-ahead-predictions using PSIS

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multilevelcoda

multilevelcoda R package for Bayesian compositional multilevel modelling

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papaja

papaja (Preparing APA Journal Articles) is an R package that provides document formats and helper functions to produce complete APA manscripts from RMarkdown-files (PDF and Word documents).

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stroop_effect_variation

Analyse between person variation of the Stroop effect

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webSDM

Model and predicts species accounting for their known trophic interaction network

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