gwpca.cv.contrib
(Package: GWmodel) :
Cross-validation data at each observation location for a GWPCA
This function finds the cross-validation data at each observation location for a basic or robust GWPCA with a specified bandwidth. Can be used to detect outliers.
● Data Source:
CranContrib
● Keywords: cv, GWPCA
● Alias: gwpca.cv.contrib
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gwr.lcr
(Package: GWmodel) :
GWR with a locally-compensated ridge term
To address possible local collinearity problems in basic GWR, GWR-LCR finds local ridge parameters at affected locations (set by a user-specified threshold for the design matrix condition number).
● Data Source:
CranContrib
● Keywords: ridge, GWR
● Alias: gwr.lcr, ridge.lm
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gwr.generalised
(Package: GWmodel) :
Generalised GWR models, including Poisson and Binomial options
This function implements generalised GWR
● Data Source:
CranContrib
● Keywords: generalised, GWR
● Alias: gwr.binomial, gwr.binomial.wt, gwr.fitted, gwr.generalised, gwr.poisson, gwr.poisson.wt
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gwr.cv
(Package: GWmodel) :
Cross-validation score for a specified bandwidth for basic GWR
This function finds the cross-validation score for a specified bandwidth for basic GWR
● Data Source:
CranContrib
● Keywords: cv, GWR
● Alias: gwr.cv
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gwr.t.adjust
(Package: GWmodel) :
Adjust p-values for multiple hypothesis tests in basic GWR
Given a set of p-values from the pseudo t-tests of GWR outputs, this function returns adjusted p-values using: (a) Bonferroni, (b) Benjamini-Hochberg, (c) Benjamini-Yekutieli and (d) Fotheringham-Byrne procedures.
● Data Source:
CranContrib
● Keywords: gwr, p-values, adjustment
● Alias: gwr.t.adjust
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gwpca.cv
(Package: GWmodel) :
Cross-validation score for a specified bandwidth for GWPCA
This function finds the cross-validation score for a specified bandwidth for basic or robust GWPCA
● Data Source:
CranContrib
● Keywords: cv, GWPCA
● Alias: gwpca.cv
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writeGWR
(Package: GWmodel) :
Write the GWR results
This function writes the calibration result of function gwr.basic to a text file and shape files
● Data Source:
CranContrib
● Keywords: gwr, write
● Alias: writeGWR
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gwr.predict
(Package: GWmodel) :
GWR used as a spatial predictor
This function implements basic GWR as a spatial predictor. The GWR prediction function is able to do leave-out-one predictions (when the observation locations are used for prediction) and predictions at a set-aside data set(when the new locations are used for prediction). It is also able to reproduce the global OLS regression prediction results.
● Data Source:
CranContrib
● Keywords: GWR, prediction
● Alias: gw.reg1, gwr.predict
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bw.ggwr
(Package: GWmodel) :
Bandwidth selection for generalised geographically weighted regression (GWR)
A function for bandwidth selection to calibrate a generalised GWR model
● Data Source:
CranContrib
● Keywords: bandwidth
● Alias: bw.ggwr, ggwr.aic
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gwr.collin.diagno
(Package: GWmodel) :
Local collinearity diagnostics for basic GWR
This function provides a series of local collinearity diagnostics for the independent variables of a basic GWR model.
● Data Source:
CranContrib
● Keywords: collinearity,diagnostic, GWR
● Alias: gwr.collin.diagno
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