Blog Archives

Aki’s favorite scientific books (so far)

May 14, 2018
By
Aki’s favorite scientific books (so far)

A month ago I (Aki) started a series of tweets about “scientific books which have had big influence on me…”. They are partially in time order, but I can’t remember the exact order. I may have forgotten some, and some stretched the original idea, but I can recommend all of them. I have collected all […] The post Aki’s favorite scientific books (so far) appeared first on Statistical Modeling, Causal…

Read more »

The curse of dimensionality and finite vs. asymptotic convergence results

February 17, 2018
By
The curse of dimensionality and finite vs. asymptotic convergence results

Related to our (Aki, Andrew, Jonah) Pareto smoothed importance sampling paper I (Aki) received a few times a comment that why bother with Pareto smoothing as you can always choose the proposal distribution so that importance ratios are bounded and then central limit theorem holds. The curse of dimensionality here is that the papers they […] The post The curse of dimensionality and finite vs. asymptotic convergence results appeared first…

Read more »

Stacking and multiverse

January 27, 2018
By

It’s a coincidence that there is another multiverse posting today. Recently Tim Disher asked in Stan discussion forum a question “Multiverse analysis – concatenating posteriors?” Tim refers to a paper “Increasing Transparency Through a Multiverse Analysis” by Sara Steegen, Francis Tuerlinckx, Andrew Gelman, and Wolf Vanpaemel. The abstract says Empirical research inevitably includes constructing a […] The post Stacking and multiverse appeared first on Statistical Modeling, Causal Inference, and Social…

Read more »

StanCon 2018 Helsinki, 29-31 August 2018

January 17, 2018
By
StanCon 2018 Helsinki, 29-31 August 2018

Photo (c) Visit Helsinki / Jussi Hellsten StanCon 2018 Asilomar was so much fun that we are organizing StanCon 2018 Helsinki August 29-31, 2018 at Aalto University, Helsinki, Finland (location chosen using antithetic sampling). Full information is available at StanCon 2018 Helsinki website Summary of the information What: One day of tutorials and two days […] The post StanCon 2018 Helsinki, 29-31 August 2018 appeared first on Statistical Modeling, Causal…

Read more »

Custom Distribution Solutions

November 21, 2017
By
Custom Distribution Solutions

I (Aki) recently made a case study that demonstrates how to implement user defined probability functions in Stan language (case study, git repo). As an example I use the generalized Pareto distribution (GPD) to model extreme values of geomagnetic storm data from the World Data Center for Geomagnetism. Stan has had support for user defined […] The post Custom Distribution Solutions appeared first on Statistical Modeling, Causal Inference, and Social…

Read more »

Postdoc in Finland and NY to work on probabilistic inference and Stan!

October 13, 2017
By

I (Aki) got 2 year funding to hire a postdoc to work on validation of probabilistic inference approaches and model selection in Stan. Work would be done with Stan team in Aalto, Helsinki and Columbia, New York. We probably have PhD positions, too. The funding is part of the joint project with Antti Honkela and […] The post Postdoc in Finland and NY to work on probabilistic inference and Stan!…

Read more »

Tenure-Track or Tenured Prof. in Machine Learning in Aalto, Finland

October 9, 2017
By

This job advertisement for a position in Aalto, Finland, is by Aki We are looking for a professor to either further strengthen our strong research fields, with keywords including statistical machine learning, probabilistic modelling, Bayesian inference, kernel methods, computational statistics, or complementing them with deep learning. Collaboration with other fields is welcome, with local opportunities […] The post Tenure-Track or Tenured Prof. in Machine Learning in Aalto, Finland appeared first…

Read more »

Stacking, pseudo-BMA, and AIC type weights for combining Bayesian predictive distributions

April 11, 2017
By
Stacking, pseudo-BMA, and AIC type weights for combining Bayesian predictive distributions

This post is by Aki. We have often been asked in the Stan user forum how to do model combination for Stan models. Bayesian model averaging (BMA) by computing marginal likelihoods is challenging in theory and even more challenging in practice using only the MCMC samples obtained from the full model posteriors. Some users have […] The post Stacking, pseudo-BMA, and AIC type weights for combining Bayesian predictive distributions appeared…

Read more »

Research fellow, postdoc, and PhD positions in probabilistic modeling and machine learning in Finland

February 28, 2017
By

Probabilistic modeling and machine learning are strong in Finland. Now is your opportunity to join us in this cool country! There are several postdoc and research fellow positions open in probabilistic machine learning in Aalto University and University of Helsinki (deadline Marh 19). Some of the topics are related also to probabilistic programming and Stan […] The post Research fellow, postdoc, and PhD positions in probabilistic modeling and machine learning…

Read more »

Practical Bayesian model evaluation in Stan and rstanarm using leave-one-out cross-validation

October 21, 2016
By

Our (Aki, Andrew and Jonah) paper Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC was recently published in Statistics and Computing. In the paper we show why it’s better to use LOO instead of WAIC for model evaluation how to compute LOO quickly and reliably using the full posterior sample how Pareto smoothing importance […] The post Practical Bayesian model evaluation in Stan and rstanarm using leave-one-out cross-validation appeared…

Read more »


Subscribe

Email:

  Subscribe