## Metadata - Author: [[tim-sumner|Tim Sumner]] - Full Title:: Stein’s Paradox - Category:: #🗞️Articles - Document Tags:: [[statistics|Statistics]], - URL:: https://substack.com/redirect/4a26b00e-429b-499f-8d64-ca9c145cc7d0?j=eyJ1IjoiNDRpMmEifQ.txKr3BEB06jM7pp-5wphmyXof7jFdPvpfRX5kIjhK8g - Finished date:: [[2024-10-11]] ## Highlights > The idea behind the James-Stein estimator is to “shrink” individual sample means toward a central value (the grand mean), which reduces the overall estimation error. ([View Highlight](https://read.readwise.io/read/01j9xsg04a3gpvfz95xxh3hefg)) > The general formula[3] for the James-Stein estimator is: >  > Where: > • **x** is the sample mean vector. > • *μ* is the grand mean (the average of the sample means). > • *c* is a shrinkage factor that lies between 0 and 1. It determines how much we pull the individual means toward the grand mean. ([View Highlight](https://read.readwise.io/read/01j9xsfndtpke14d2dene7cr4w))