Jun 22, 2023
7 mins
Tag:
__conference__
Last month I was at WashU campus for the Bayesian-for-nuclear-physics workshop. Today I am in WashU again: This time it is for StanCon 2023. Here is some of the random takeaway I obtain from the...

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May 26, 2023
7 mins
Tag:
__modeling__
The myth A few years ago I saw a StackOverflow question (but I cannot find it now): allegedly Andrew Gelman blogged that Bayesian models would not overfit and would only underfit (I also cannot find...

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Dec 30, 2022
4 mins
Tag:
__zombie__
I came across this book called “Die with zero”. Along with many other yolo ideas, the book prompts the attitude that one must maximize net fulfillment over net worth to the extent of “DIE WITH...

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Dec 08, 2022
1 min
Tag:
__computing__
In Bayesian computation, we use control variate to reduces Monte Carlo (MC) variance. The idea if we want to compute $E_{p} h(x)$ from MC draws $x_{1, \dots, S}$, instead of computing the sample mean of...

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Aug 23, 2022
2 mins
Tag:
__stan__
Consider a normal-normal model with vector data $y$ and scalar parameter $\mu$ and $\sigma$ written in the following stan code1: Bob Carpenter wrote the code. Bob, Charles and I wasted one hour discussing this toy...

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Aug 22, 2022
3 mins
Tag:
__modeling__
Sometimes a model can be decomposed into modules and we may run inference separately. This task comes a lot in cut-feedback, SMC, causal inference (two stage regression), multiple imputation, and PK-PD modeling.

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Aug 20, 2022
5 mins
Tag:
__prediction__
Score matching Suppose that we observe a sequence of data $y={y_i \in R_m \mid 1\leq i \leq n}$ coming independently from an unknown distribution $p_{true}$; we would like to evaluate a forecast given by a...

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Apr 19, 2022
2 mins
Tag:
__computing__
Quiz: you are given ONE random draw $x$ that was drawn from a density $p(x)$. Could you produce an unbiased estimate of $1/E_p[X]$?

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Mar 29, 2022
3 mins
Tag:
__computing__
I have not done any math for a long while. Today I happen to need to compute an integral

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Nov 22, 2021
3 mins
Tag:
__modeling__
I read an arxiv preprint “History and Nature of the Jeffreys-Lindley Paradox” by Eric-Jan Wagenmakers and Alexander Ly. It is a comprehensive journey that reviews the development of the “Jeffreys-Lindley Paradox”, or what is typically...

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Oct 05, 2021
2 mins
Tag:
__computation__
I come across a paper “The Adaptive Biasing Force Method: Everything You Always Wanted To Know but Were Afraid To Ask” by Jeffrey Comer et al. When comparing the adaptive biasing force method (gradient based...

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Sep 15, 2021
2 mins
Tag:
__visualization__
Why do we automatically read that 6'3 >> 5'8, while 52% ≈ 47%?

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Aug 19, 2021
3 mins
Tag:
__modeling__
Assuming there are some hyperparameters $\beta$ in the model involving data $y$. We have four ways to get some inference of $\beta$.

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Jun 04, 2021
4 mins
Tag:
__decision theory__
One mental challenge is decision-making with more than two options. To simplify the dilemma that your humble author is encountering, assume that it is on a long haul flight and you are asked by a...

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May 23, 2021
6 mins
Tag:
__causal__

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