Category: StanPage 1 of 3

Addressing degeneracy

Loosely speaking, the followings are all related Fisher information matrix (FIM) is not positive definite nonidentifiable/singularities of a statistical model algebraically: map from a parameter (theta) to a…

Workflow network (1): adding inference algorithm choice for multiverse analysis

The three main themes for my research on simulation on generative model classes are as follows with related literature: A. interaction between reality and hyperreality (simulation) on Bayesian workflow…

Bayesian workflow in Stan

I gave a talk on Bayesian workflow in Stan. It includes recommendations on defining “what” problems to solve and “how” to solve with one’s and community’s resources. This…

Divergent transitions in Stan

Why is divergent trasition bad? divergent transitions result in a biased sample – at the end of a divergent transition, the parameter estimates are unchanged, effectively, the same…

MCMCseminar on sampler conditions#1

I gave a talk on Title: Howtoproveyoursamplerisgood?#1 Findmetrictoproveconvergence slides: https://docs.google.com/presentation/d/1dLiLVRFKoisOKXfJ5dDZikOMxz51CIDsy4tGtrE-7HE/edit?usp=sharing

MCMCseminar on hyperbolic space

I gave a talk on hyperbolic space, its application in structure data, and how to design its sampler. The key lies in designing a metric and latent space….

My academic interests in 2021

One of my academic goal is to establish a Bayesian risk management workflow in operations research, especially for the defense industry where I have great project opportunities through…

Decision analysis using Stan

The current model in here is for prediction ie. the result is the optimal parameter value that minimizes the distance between prediction and real data. My goal is…

Stochastic optimization in variational inference

I am trying to making stan’s advi engine more robust in terms of the following: stopping rule values returned from each iteration 1 is decided based on 2…

Time series, multimodal, mixture model, variational methods

I wish to solve multimodal distribution optimization in two stage approach. Example usecase is newsvendor problem; order quantity should be optimized for the multimodal-shaped demand due to its…