# What is the optimal design of regression covariates?

Feb 23, 2021
Depends who you ask.

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Bayesian Statistics, Machine Learning

Depends who you ask.

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I was reading Peter Bühlmann’s statistical science article “Invariance, Causality and Robustness”. To be fair, he gave a short course in 2020 here in Columbia, but after reading this paper I guess I did not...

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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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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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The likelihood principle is often phrase as an axiom in Bayesian statistics. My interpretation of the likelihood principle reads:

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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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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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This is wrong. Indeed it can be opposite.

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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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in general B-spline is sensitive to the boundary knots, while the unknown support of latent variable models amplifies such sensitivity.

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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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I took this seminar class on Large Deviation Principle (LDP) by Sumit. I summarize some following results that I personally think most relevant (to what I am doing now). Most results are from the book...

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M asked me a question which essentially looks like this: In a mediation model a and b are regression coefficient through the mediation path, and the final quantity of interest is therefore the product $ab$....

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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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On the brighter side, Ronald Reagan was 21 and looking for work in 1932, one of the worst years of the Great Depression, who later said "To be young in my generation was to feel that your future had been mortgaged out from under you, and that's a tragic mistake...

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