Best point mass approximation

Feb 20, 2021       1 mins     Tag: computation
It comes a lot that we often summarize a continuous distribution (often, posterior distribution of parameter estimation or of predictions) by a point mass (or a sharpe spike) for (1) computation or memory cost, (2)...
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Measuring extrapolation

Feb 19, 2021       7 mins     Tag: modeling causal
Cramér–Rao lower bound I will not call myself a theoretic statistician but sometimes I still find mathematical statistics amusing especially when they have practical implications. To start this blog post, I will go from Cramér–Rao...
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Monte Carlo estimate of quantile

Nov 24, 2020       4 mins     Tag: computation
This comes a lot in Monte Carlo computation: we are only given finite draws but we want to compute extreme quantiles.
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Book review "Discrete Distribution"

Nov 21, 2020       2 mins     Tag: book
Today I was reading the book “Discrete Distribution” by Johnson and Kotz. I did not realize it has a newer version until I started this blog post—-the edition I read was published in 1969 by...
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Why Bayesian models could have better predictions.

Sep 28, 2020       2 mins     Tag: modeling
In a predictive paradigm, no one really cares about how I obtain the estimation or the prediction. It can come from some MLE, MAP of risk minimization, or some Bayes procedure. Also, when we talk...
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Gaussian process regressions having opinions or speculation.

May 19, 2020       3 mins     Tag: zombie modeling
I occasionally read Howard Marks’s memo, and in my recent infrequent visit, I have constantly encountered him citing Marc Lipsitch, Professor of Epidemiology at Harvard, that (in Lipsitch’s covid research and in Marks’s money making)...
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Back to January 18 when there were 60 cases globally

May 03, 2020       3 mins     Tag: decision-theory
On January 18 2020, the pre-pandemic era, when the stock market in both US and China was still busy celebrating their phase-one trade deal, I saw this news in the China section of BBC which...
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