AdaptiveEstimator Class Reference

#include <AdaptiveEstimator.h>

Inheritance diagram for AdaptiveEstimator:

Public Member Functions
std::vector< double >	query (VectorXd q)
void	setMedians (int l)

Public Attributes
double	totalTime = 0

Protected Member Functions
virtual std::vector< double >	evaluateQuery (VectorXd q, int level)=0

Protected Attributes
int	numPoints
double	gamma = 0.5
int	I
int	L = 3
std::vector< double >	mui
std::vector< int >	Mi
std::vector< double >	ti
std::vector< int >	ki
std::vector< double >	wi
double	r
std::string	EXP_STR = "exp"

Detailed Description

Base class for the adaptive sampling procedure. Subclasses can be implemented via estimators like HBE and RS.

Member Function Documentation

evaluateQuery()

virtual std::vector<double> AdaptiveEstimator::evaluateQuery ( VectorXd  q, int  level  )

protectedpure virtual

For subclasses to implement: evaluate density of query q at the given level.

Implemented in AdaptiveRSDiag, AdaptiveHBE, and AdaptiveRS.

query()

std::vector<double> AdaptiveEstimator::query ( VectorXd  q )

inline

Estimate density of query q via adaptively sampling.

Member Data Documentation

gamma

double AdaptiveEstimator::gamma = 0.5

protected

decay rate of target density between each level

I

int AdaptiveEstimator::I

protected

number of levels

ki

std::vector<int> AdaptiveEstimator::ki

protected

hashing scheme parameter for level i: # hash functions

L

int AdaptiveEstimator::L = 3

protected

median of L means

Mi

std::vector<int> AdaptiveEstimator::Mi

protected

samples for level i

mui

std::vector<double> AdaptiveEstimator::mui

protected

target density of the level i

r

double AdaptiveEstimator::r

protected

Effective diameter sqrt(log(1/ tau))

wi

std::vector<double> AdaptiveEstimator::wi

protected

hashing scheme parameter for level i: binWidth

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

• AdaptiveEstimator.h