Yo, listen up, here's a story
About a little guy that lives in a BLUE world
And all day and all night and everything he sees is just Best Linear Unbiased Estimator
To the practicing statisticians out there: Is BLUE at all relevant in the field? Even if you can formulate your data/problem as a linear regression, wouldn't maximum likelihood estimation still be the preferred method in most scenarios?
Edit: Of course Bayesian analysis is of equal relevance here!
OLS is well used in a lot of domains. If you have a continuous outcome you have a straightforward and very easy way to get a quick reliable estimate of some interesting parameter. The typical use in most social sciences is to implement some sort of difference-in-differences (or DiD event-study) estimate within a simple linear regression.
5 Comments
Bishma@discuss.tchncs.de · 7 pts · 332d
Yo, listen up, here's a story
About a little guy that lives in a BLUE world
And all day and all night and everything he sees is just Best Linear Unbiased Estimator
Da-ba-dee, da-ba-di, da-ba-dee, da-ba-di
benni@lemmy.world · 5 pts · 331d
I don't get it, can you explain?
driving_crooner@lemmy.eco.br · 5 pts · 331d
https://en.m.wikipedia.org/wiki/Best_linear_unbiased_prediction
https://en.m.wikipedia.org/wiki/Gauss%E2%80%93Markov_theorem
montechristo@feddit.org · 2 pts · 331d
To the practicing statisticians out there: Is BLUE at all relevant in the field? Even if you can formulate your data/problem as a linear regression, wouldn't maximum likelihood estimation still be the preferred method in most scenarios? Edit: Of course Bayesian analysis is of equal relevance here!
merari42@lemmy.world · 1 pts · 331d
OLS is well used in a lot of domains. If you have a continuous outcome you have a straightforward and very easy way to get a quick reliable estimate of some interesting parameter. The typical use in most social sciences is to implement some sort of difference-in-differences (or DiD event-study) estimate within a simple linear regression.