Skip to content

shashank-shekhar/regressionPy

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 

Repository files navigation

regressionPy

Minimum empirical square error estimator

The code solves this question :

Consider the following probability density function on hx; yi. f (x) = Uniform[-2; 2] and f (y|x) = N(u,sigma^2) where u=0.3x^3-0.6x^2+0.05x-3 and sigma =0.25 Generate 20 i.i.d samples from this distribution. Now find the minimum empirical square error estimator from the class of all 3rd degree polynomials. Do the same for the class of all 5th degree polynomials. Plot the data superimposed with the two polynomials. Report the polynomials and the error in both cases.

About

Minimum empirical square error estimator

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages