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#include <JohnsonKDESmoother.hh>
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| JohnsonKDESmoother (unsigned nbins, double xmin, double xmax, int symbetaPower, double bwFactor=1.0, const char *label=0) |
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int | symbetaPower () const |
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double | bwFactor () const |
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| AbsMarginalSmootherBase (unsigned nbins, double xmin, double xmax, const char *axisLabel=0) |
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void | setAxisLabel (const char *axisLabel) |
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unsigned | nBins () const |
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double | xMin () const |
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double | xMax () const |
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double | binWidth () const |
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const std::string & | getAxisLabel () const |
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gs::AbsArchive * | getArchive () const |
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const std::string & | getArchiveCategory () const |
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double | lastBandwidth () const |
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void | setArchive (gs::AbsArchive *ar, const char *category=0) |
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void | unsetArchive () |
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template<typename Numeric > |
const HistoND< double > & | smooth (const std::vector< Numeric > &inputPoints, double minValue=-std::numeric_limits< double >::max(), double maxValue=std::numeric_limits< double >::max(), double *bandwidthUsed=0) |
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template<typename Numeric > |
const HistoND< double > & | smooth (unsigned long uniqueId, unsigned dimNumber, const std::vector< Numeric > &inputPoints, double minValue=-std::numeric_limits< double >::max(), double maxValue=std::numeric_limits< double >::max(), double *bandwidthUsed=0) |
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template<typename Numeric > |
const HistoND< double > & | weightedSmooth (const std::vector< std::pair< Numeric, double > > &inputPoints, double minValue=-std::numeric_limits< double >::max(), double maxValue=std::numeric_limits< double >::max(), double *bandwidthUsed=0) |
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template<typename Numeric > |
const HistoND< double > & | weightedSmooth (unsigned long uniqueId, unsigned multivariatePointDimNumber, const std::vector< std::pair< Numeric, double > > &inputPoints, double minValue=-std::numeric_limits< double >::max(), double maxValue=std::numeric_limits< double >::max(), double *bandwidthUsed=0) |
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1-d KDE implementation with adaptive bandwidth. The adaptive bandwidth for each data point is set in inverse proportion to the square root of the pilot density at that point. The pilot density bandwidth is calculated with Johnson system densities used as reference distributions for AMISE optimization. The fit of Johnson densities to the data sample is done by matching sample moments to the curve moments.
◆ JohnsonKDESmoother()
npstat::JohnsonKDESmoother::JohnsonKDESmoother |
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unsigned |
nbins, |
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double |
xmin, |
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double |
xmax, |
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int |
symbetaPower, |
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double |
bwFactor = 1.0 , |
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const char * |
label = 0 |
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Constructor arguments are as follows:
nbins, xmin, xmax – Parameters for the histogram which will be accumulated using the data sample to be smoothed.
symbetaPower – Power of the symmetric beta kernel to use. Gaussian kernel will be used in case this parameter is negative. This parameter must not exceed 10.
bwFactor – Fudge factor for the plugin bandwidth used for the pilot and final density estimates.
label – Label for the axis. Useful in case smoothing results are stored for inspection.
◆ symbetaPower()
int npstat::JohnsonKDESmoother::symbetaPower |
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const |
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inline |
Simple inspector of object properties
The documentation for this class was generated from the following file:
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