#include <LocalQuantileRegression.hh>
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void | resetAccumulators () |
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const QuadraticOrthoPolyND & | poly_ |
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BoxND< Numeric > | regressionBox_ |
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std::vector< double > | location_ |
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std::vector< double > | scale_ |
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std::vector< double > | coords_ |
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std::vector< double > | coeffs_ |
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long double | loss_ |
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const double | quantile_ |
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const double | onemq_ |
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const unsigned | mydim_ |
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template<class Numeric>
class npstat::QuantileRegressionBase< Numeric >
Base class for quantile regression
◆ dim()
Inspect object properties
◆ empiricalC0()
This method will provide a guess for the 0th order coefficient of the regression polynomial. It will also calculate the effective number of points inside the current regression box.
◆ linearLoss()
This method calculates the function that has to be minimized; the minimization itself is up to some external optimization engine.
◆ setLinearMapping()
template<class Numeric >
void npstat::QuantileRegressionBase< Numeric >::setLinearMapping |
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const double * |
location, |
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const double * |
scale, |
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unsigned |
locationAndScaleArraySize |
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This method sets up a mapping from the fitted region into the region which was used to create the orthogonal polynomials. The mapping is linear in every coordinate separately: ortho[i] = fitted[i]*scale[i] + location[i]. Note that the "setRegressionBox" method automatically sets up the default mapping which will be adequate for most applications.
◆ setRegressionBox()
Only the data inside the regression box will be used in the fit (and some points may be subsequently weighted down to zero by the weigh function).
Note that the "setRegressionBox" method automatically sets up the standard mapping: the edges of the regression box are mapped into the boundaries which were used to create the orthogonal polynomials. If the standard mapping is not what you want (for example, this might be the case near the boundaries of the fitted region), you must call "setLinearMapping" after calling "setRegressionBox" in order to override the standard mapping.
This method must be called at least once after the object is constructed and before any call to "linearLoss".
The documentation for this class was generated from the following file: