MultiDimesional fitting.
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#include <yat/regression/MultiDimensionalWeighted.h>
◆ chisq()
double theplu::yat::regression::MultiDimensionalWeighted::chisq |
( |
void |
| ) |
const |
- Returns
- sum of squared residuals
◆ fit()
- See also
- gsl_multifit_wlinear
- Exceptions
-
A | GSL_error exception is thrown if memory allocation fails or the underlying GSL calls fails (usually matrix dimension errors). |
◆ fit_parameters()
const utility::Vector& theplu::yat::regression::MultiDimensionalWeighted::fit_parameters |
( |
void |
| ) |
const |
- Returns
- parameters of fitted model
◆ predict()
double theplu::yat::regression::MultiDimensionalWeighted::predict |
( |
const utility::VectorBase & |
x | ) |
const |
- Returns
- value in x according to fitted model
◆ prediction_error2()
double theplu::yat::regression::MultiDimensionalWeighted::prediction_error2 |
( |
const utility::VectorBase & |
x, |
|
|
const double |
w = 1 |
|
) |
| const |
- Returns
- expected squared prediction error for a new data point in x
◆ s2()
double theplu::yat::regression::MultiDimensionalWeighted::s2 |
( |
const double |
w = 1.0 | ) |
const |
- Returns
- variance of residuals
◆ standard_error2()
double theplu::yat::regression::MultiDimensionalWeighted::standard_error2 |
( |
const utility::VectorBase & |
x | ) |
const |
- Returns
- error of model value in x
The documentation for this class was generated from the following file: