Class GWRGeneralized

Defined in File GWRGeneralized.h

Inheritance Relationships

Base Types

public gwm::GWRBase (Class GWRBase)
public gwm::IBandwidthSelectable (Struct IBandwidthSelectable)
public gwm::IParallelizable (Struct IParallelizable)
public gwm::IParallelOpenmpEnabled (Struct IParallelOpenmpEnabled)

Class Documentation

class GWRGeneralized : public gwm::GWRBase, public gwm::IBandwidthSelectable, public gwm::IParallelizable, public gwm::IParallelOpenmpEnabled 

Generalized GWR.

Public Types

enum Family

Family of generalized model.

Values:

enumerator Poisson: Poisson model.

enumerator Binomial: Binomial model.

enum BandwidthSelectionCriterionType

Get type of criterion for bandwidth selection. BandwidthSelectionCriterionType Type of criterion for bandwidth selection.

Values:

enumerator AIC: AIC.

enumerator CV: CV.

typedef double (GWRGeneralized::* BandwidthSelectCriterionFunction)(BandwidthWeight*): Calculator to get criterion for bandwidth optimization.

typedef arma::mat (GWRGeneralized::* GGWRfitFunction)(const arma::mat &x, const arma::vec &y): Calculator for fitting.

typedef arma::vec (GWRGeneralized::* CalWtFunction)(const arma::mat &x, const arma::vec &y, arma::mat w): Calculator for weighting.

Public Functions

inline GWRGeneralized(): Construct a new GWRGeneralized object.

inline ~GWRGeneralized(): Destroy the GWRGeneralized object.

inline virtual Status getCriterion(BandwidthWeight *bandwidthWeight, double &criterion) override

Get criterion value with given bandwidth for bandwidth optimization.

Parameters:

weight – Given bandwidth.
criterion – [out] Criterion value.

Returns:

Status Algorithm status.

virtual arma::mat predict(const arma::mat &locations) override

Predict coefficients on specified locations.

Parameters:: locations – Locations where to predict coefficients.
Returns:: mat Predicted coefficients.

virtual arma::mat fit() override

Fit coefficient estimates.

Returns:: mat Coefficient estimates

arma::mat fit(const arma::mat &x, const arma::vec &y, arma::mat &betasSE, arma::vec &shat, arma::vec &qdiag, arma::mat &S)

inline virtual int parallelAbility() const override

Return the parallel ability of this algorithm.

Returns:: Bitwise OR of aviliable parallel types of this algorithm.

inline virtual ParallelType parallelType() const override

Return the parallel type of this algorithm.

Returns:: Parallel type of this algorithm

virtual void setParallelType(const ParallelType &type) override

Set the parallel type of this algorithm.

Parameters:: type – Parallel type of this algorithm.

inline virtual void setOmpThreadNum(const int threadNum) override

Set the thread numbers while paralleling.

Parameters:: threadNum – Number of threads.

inline Family getFamily() const: Get the family of the model. Family of the model.

bool setFamily(Family family): Set the family of the model. Family of the model.

inline double getTol() const: Get the tolerance. Tolerance.

inline void setTol(double tol): Set the tolerance. Tolerance.

inline size_t getMaxiter() const: Get the maximum of iteration. Maximum of iteration.

inline void setMaxiter(std::size_t maxiter): Set the maximum of iteration. Maximum of iteration.

inline const arma::mat &getWtMat1() const

inline const arma::mat &getWtMat2() const

inline GWRGeneralizedDiagnostic getDiagnostic() const: Get the diagnostic information. Diagnostic information.

inline GLMDiagnostic getGLMDiagnostic() const: Get the diagnostic information of generalized linear model. Diagnostic information.

void setBandwidthSelectionCriterionType(const BandwidthSelectionCriterionType &bandwidthSelectionCriterionType)

inline BandwidthCriterionList bandwidthSelectorCriterions() const

inline BandwidthSelectionCriterionType bandwidthSelectionCriterionType() const

inline bool autoselectBandwidth() const: Get whether bandwidth optimization is enabled. Yes No.

inline void setIsAutoselectBandwidth(bool value): Set whether bandwidth optimization is enabled. Whether bandwidth optimization is enabled.

inline arma::mat regressionData() const

inline void setRegressionData(const arma::mat &locations)

inline bool hasHatMatrix() const: Get whether has hat matrix. Yes No.

inline void setHasHatMatrix(bool value): Set whether has hat matrix. Whether has hat matrix.

inline bool hasRegressionData() const

inline void setHasRegressionData(bool value)

Public Members

BandwidthCriterionList mBandwidthSelectionCriterionList

Public Static Functions

static arma::vec gwPredict(const arma::mat &x, const arma::vec &y, const arma::vec &w): Geographically weighted predicting. Independent variables Dependent variables Weights Coefficient estimates.

static arma::vec gwFit(const arma::mat &x, const arma::vec &y, const arma::vec &w, arma::uword focus, arma::mat &ci, arma::mat &s_ri): Geographically weighted fitting. Independent variables Dependent variables Weights Index of focused sample Coefficient estimates.

static arma::mat dpois(arma::mat y, arma::mat mu)

static arma::mat dbinom(arma::mat y, arma::mat m, arma::mat mu)

static arma::mat lchoose(arma::mat n, arma::mat k)

static arma::mat lgammafn(arma::mat x)

static arma::mat CiMat(const arma::mat &x, const arma::vec &w)

Protected Functions

arma::mat fitPoissonSerial(const arma::mat &x, const arma::vec &y): Serial implementation of fitting Poisson model. Independent variables Dependent variables Coefficient estimates.

arma::mat fitBinomialSerial(const arma::mat &x, const arma::vec &y): Serial implementation of fitting Binomial model. Independent variables Dependent variables Coefficient estimates.

arma::mat diag(arma::mat a)

arma::vec PoissonWtSerial(const arma::mat &x, const arma::vec &y, arma::mat w): Serial implementation of fitting weighted Poisson model. Independent variables Dependent variables Weights Coefficient estimates.

arma::vec BinomialWtSerial(const arma::mat &x, const arma::vec &y, arma::mat w): Serial implementation of fitting weighted Binomial model.

void CalGLMModel(const arma::mat &x, const arma::vec &y)

Protected Attributes

Family mFamily: Family of the model.

double mTol = 1e-5: Tolerance.

std::size_t mMaxiter = 20: Maximum of iteration.

bool mHasHatMatrix = true: Whether has hat matrix.

bool mHasRegressionData = false

arma::mat mBetasSE: //!< Standard error of coefficient estimates

arma::vec mShat: //!< A vector of trace of \(S\) and \(S'S\)

arma::mat mS: //!< Hat matrix \(S\)

double mGwDev

arma::mat mRegressionData

arma::mat mWtMat1

arma::mat mWtMat2

GWRGeneralizedDiagnostic mDiagnostic: Diagnostic information.

GLMDiagnostic mGLMDiagnostic: Diagnostic information for GLM.

arma::mat mWt2

arma::mat myAdj

double mLLik = 0: Logorithm of likelihood.

GGWRfitFunction mGGWRfitFunction = &GWRGeneralized::fitPoissonSerial : Calculator for fitting.

CalWtFunction mCalWtFunction = &GWRGeneralized::PoissonWtSerial : Calculator for weighting.

bool mIsAutoselectBandwidth = false: Whether bandwidth optimization is enabled.

BandwidthSelectionCriterionType mBandwidthSelectionCriterionType = BandwidthSelectionCriterionType::AIC : Type of criterion for bandwidth optimization.

BandwidthSelectCriterionFunction mBandwidthSelectCriterionFunction = &GWRGeneralized::bandwidthSizeGGWRCriterionCVSerial: Calculator to get criterion for given bandwidth value.

BandwidthSelector mBandwidthSizeSelector: Bandwidth size selector.

double mBandwidthLastCriterion = DBL_MAX: Last criterion for bandwidth selection.

ParallelType mParallelType = ParallelType::SerialOnly : Type of parallelization.

int mOmpThreadNum = 8: Number of threads used in multithreading.