PLearn::SharpeRatioStatsIterator Class Reference

#include <StatsIterator.h>

Inheritance diagram for PLearn::SharpeRatioStatsIterator:

[legend]Collaboration diagram for PLearn::SharpeRatioStatsIterator:

[legend]List of all members.

Public Member Functions
virtual string	info () const
	returns a bit more informative string about object (default returns classname())
virtual void	init (int inputsize)
	Call this method once with the correct inputsize.
virtual void	update (const Vec &input)
	Then iterate over the data set and call this method for each row.
virtual bool	finish ()
	PLEARN_DECLARE_OBJECT (SharpeRatioStatsIterator)
virtual void	makeDeepCopyFromShallowCopy (map< const void *, void * > &copies)
virtual void	oldwrite (ostream &out) const
virtual void	oldread (istream &in)
	DEPRECATED For backward compatibility with old saved object.
Static Protected Member Functions
void	declareOptions (OptionList &ol)
	redefine this in subclasses: call declareOption(...) for each option, and then call inherited::declareOptions(options) ( see the declareOption function further down)
Protected Attributes
Vec	nnonzero
Vec	meansquared
Vec	mean
Private Types
typedef StatsIterator	inherited

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Detailed Description

Compute the Sharpe ratio = mean(profit) / stdev(profit) where profit is assumed to be the "cost" given in input. Note that the mean and stdev are only computed over the instances where profit!=0 (because these represent the actual transactions that occured).

Definition at line 217 of file StatsIterator.h.

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Member Typedef Documentation

typedef StatsIterator PLearn::SharpeRatioStatsIterator::inherited [private]

Reimplemented from PLearn::StatsIterator. Definition at line 219 of file StatsIterator.h.

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Member Function Documentation

void PLearn::SharpeRatioStatsIterator::declareOptions (  OptionList &  ol  )  [static, protected]

redefine this in subclasses: call declareOption(...) for each option, and then call inherited::declareOptions(options) ( see the declareOption function further down) ex: static void declareOptions(OptionList& ol) { declareOption(ol, "inputsize", &MyObject::inputsize_, OptionBase::buildoption, "the size of the input\n it must be provided"); declareOption(ol, "weights", &MyObject::weights, OptionBase::learntoption, "the learnt model weights"); inherited::declareOptions(ol); } Reimplemented from PLearn::StatsIterator. Definition at line 387 of file StatsIterator.cc. References PLearn::declareOption(), and PLearn::OptionList.

bool PLearn::SharpeRatioStatsIterator::finish (   )  [virtual]

Call this method when all the data has been shown (through update) If the method returns false, then a further pass through the data is required. Implements PLearn::StatsIterator. Definition at line 378 of file StatsIterator.cc. References mean, meansquared, nnonzero, PLearn::sqrt(), and PLearn::squareSubtract().

virtual string PLearn::SharpeRatioStatsIterator::info (   )  const [inline, virtual]

returns a bit more informative string about object (default returns classname()) Reimplemented from PLearn::Object. Definition at line 227 of file StatsIterator.h.

void PLearn::SharpeRatioStatsIterator::init (  int  inputsize  )  [virtual]

Call this method once with the correct inputsize. Implements PLearn::StatsIterator. Definition at line 357 of file StatsIterator.cc. References mean, meansquared, nnonzero, and PLearn::Vec.

void PLearn::SharpeRatioStatsIterator::makeDeepCopyFromShallowCopy (  map< const void *, void * > &  copies  )  [virtual]

Reimplemented from PLearn::StatsIterator. Definition at line 350 of file StatsIterator.cc. References PLearn::deepCopyField(), mean, and meansquared.

void PLearn::SharpeRatioStatsIterator::oldread (  istream &  in  )  [virtual]

DEPRECATED For backward compatibility with old saved object. Reimplemented from PLearn::StatsIterator. Definition at line 411 of file StatsIterator.cc. References mean, meansquared, nnonzero, PLearn::readField(), PLearn::readFooter(), and PLearn::readHeader().

void PLearn::SharpeRatioStatsIterator::oldwrite (  ostream &  out  )  const [virtual]

Reimplemented from PLearn::StatsIterator. Definition at line 401 of file StatsIterator.cc. References mean, meansquared, nnonzero, PLearn::writeField(), PLearn::writeFooter(), and PLearn::writeHeader().

PLearn::SharpeRatioStatsIterator::PLEARN_DECLARE_OBJECT (  SharpeRatioStatsIterator   )

void PLearn::SharpeRatioStatsIterator::update (  const Vec &  input  )  [virtual]

Then iterate over the data set and call this method for each row. Implements PLearn::StatsIterator. Definition at line 366 of file StatsIterator.cc. References PLearn::TVec< T >::length(), mean, meansquared, and nnonzero.

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Member Data Documentation

Vec PLearn::SharpeRatioStatsIterator::mean [protected]

Definition at line 224 of file StatsIterator.h. Referenced by finish(), init(), makeDeepCopyFromShallowCopy(), oldread(), oldwrite(), and update().

Vec PLearn::SharpeRatioStatsIterator::meansquared [protected]

Definition at line 223 of file StatsIterator.h. Referenced by finish(), init(), makeDeepCopyFromShallowCopy(), oldread(), oldwrite(), and update().

Vec PLearn::SharpeRatioStatsIterator::nnonzero [protected]

Definition at line 222 of file StatsIterator.h. Referenced by finish(), init(), oldread(), oldwrite(), and update().

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The documentation for this class was generated from the following files:

• StatsIterator.h
• StatsIterator.cc

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