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Implementation of B-Splines in Stan
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State space models (dynamic linear models, hidden Markov models) implemented in Stan.
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🚫 ↩️ A document that introduces Bayesian data analysis. -
Conditional autoregressive models in Stan
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Applied time series analysis in R with Stan. Allows fast Bayesian fitting of multivariate time-series models.
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MTH225 Statistics for Science Spring 2016
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Slides and assignments for an introductory course in hierarchical Bayesian modeling
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Materials for BioC-2016 workshop entitled "Introduction to Bayesian Inference using Stan with Applications to Cancer Genomics"
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A workshop on using Stan with R.
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Various models of heterogeneous treatment effects
Stan 5 -
Learning rstan: R Interface to Stan
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An analysis of Vision Zero Policies
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Bayesian hierarchical models for estimating spatial and temporal patterns in vegetation phenology from Landsat time series
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Practice Stan with simple POPPK models and virtual data
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Stancon 2018 Helsinki submission.
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Introduciton to Stan
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Models for analyzing network data in which informant reports may be in conflict
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PNBD/Stan model presented at Stanford Stan User Group March 2018
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Reanalysis of Carney, Cuddy, and Yap 2010 data on power posing.
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DynBayes
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This repo contains (some) codes for the back-calculation models discussed in the thesis "Estimating HIV incidence from multiple sources of data" by Francesco Brizzi (University of Cambridge)
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Stan models and associated R code
