Statements (32)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
gptkb:mathematical_concept
|
| gptkbp:alternativeTo |
gptkb:Method_of_moments
Maximum likelihood estimation |
| gptkbp:application |
gptkb:signal_processing
Machine learning Curve fitting Econometrics Parameter estimation |
| gptkbp:appliesTo |
gptkb:Linear_regression
Nonlinear regression |
| gptkbp:assumes |
Errors are independent
Errors have constant variance Errors are normally distributed (in classical case) |
| gptkbp:category |
mathematical optimization
Numerical analysis Estimation theory |
| gptkbp:developedBy |
gptkb:Carl_Friedrich_Gauss
gptkb:Adrien-Marie_Legendre |
| gptkbp:firstPublished |
1805
|
| gptkbp:form |
minimize sum of squared differences between observed and predicted values
|
| https://www.w3.org/2000/01/rdf-schema#label |
Method of least squares
|
| gptkbp:output |
Best-fit parameters
|
| gptkbp:purpose |
Minimize sum of squared residuals
|
| gptkbp:relatedTo |
gptkb:Ordinary_least_squares
Generalized least squares Weighted least squares Total least squares |
| gptkbp:usedIn |
gptkb:Regression_analysis
Statistics Data fitting |
| gptkbp:bfsParent |
gptkb:Wilhelm_Gauss
|
| gptkbp:bfsLayer |
6
|