Kenneth Hung
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applied statistics
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data science
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multiple testing
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Post-selection unbiased estimator
selective inference
Does a post-selection unbiased estimator for the mean of a normal distribution exist?
Dec 8, 2023
Kenneth Hung
Parametric mean estimation
applied statistics
data science
A common task in data science is mean estimation. The go-to estimator is sample mean, which is non-parametric in nature. But what if we have good reasons to believe in a parametric model for the population?
Mar 11, 2023
Kenneth Hung
Philosophy of statistics, or data science
data science
This is an ambitious title for a post, but perhaps, and I hope, every data scientist or statistician eventually has their own philosophy on what we are doing.
Sep 10, 2022
Kenneth Hung
Meta-analysis on nudging experiments
multiple testing
A recent meta-analysis on choice architecture, or “nudging”, but people do not seem to agree on if “nudging” works.
Aug 27, 2022
Kenneth Hung
Moment conditions heuristics
applied statistics
Moment conditions are common in literature, but how do we assess if they reasonably apply?
Apr 11, 2022
Kenneth Hung
Playing with Bayes and RStan
statistical computing
First time pretending to be a Bayesian, and trying RStan.
Sep 25, 2020
Kenneth Hung
Normal distribution in Python
statistical computing
Getting the hang of statistical computing in Python
Aug 4, 2020
Kenneth Hung
Binomial ranking with SARS data
multiple testing
If deaths in each country follows a binomial distribution, how do we rank them by the probability parameter?
Feb 15, 2020
Kenneth Hung
p-value screening
multiple testing
selective inference
Better multiple testing by screening p-values first, to reduce the penalty in common multiple testing procedure
Sep 21, 2018
Kenneth Hung
L1-penalized likelihood asymptotics
selective inference
Generalizing Lasso penalty to non-linear model, e.g. a binomial model.
Apr 10, 2017
Kenneth Hung
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