Man pages for gmGeostats
Geostatistics for Compositional Analysis
| accuracy | Compute accuracy and precision |
| ana | Flow anamorphosis transform Compute a transformation that... |
| anaBackward | Backward gaussian anamorphosis backward transformation to... |
| anaForward | Forward gaussian anamorphosis forward transformation to... |
| anis_GSLIBpar2A | Produce anisotropy scaling matrix from angle and anisotropy... |
| AnisotropyRangeMatrix | Force a matrix to be anisotropy range matrix, |
| AnisotropyScaling | Convert to anisotropy scaling matrix |
| as.AnisotropyRangeMatrix | Force a matrix to be anisotropy range matrix, |
| as.AnisotropyScaling | Convert to anisotropy scaling matrix |
| as.array.DataFrameStack | Convert a stacked data frame into an array |
| as.CompLinModCoReg | Recast a model to the variogram model of package... |
| as.directorVector | Express a direction as a director vector |
| as.function.gmCgram | Convert a gmCgram object to an (evaluable) function |
| as.gmCgram | Convert theoretical structural functions to gmCgram format |
| as.gmEVario | Convert empirical structural function to gmEVario format |
| as.gmSpatialModel | Recast spatial object to gmSpatialModel format |
| as.gstat | Convert a regionalized data container to gstat |
| as.gstatVariogram | Represent an empirical variogram in "gstatVariogram" format |
| as.list.DataFrameStack | Convert a stacked data frame into a list of data.frames |
| as.LMCAnisCompo | Recast compositional variogram model to format LMCAnisCompo |
| as.logratioVariogram | Recast empirical variogram to format logratioVariogram |
| as.logratioVariogramAnisotropy | Convert empirical variogram to "logratioVariogramAnisotropy" |
| as.variogramModel | Convert an LMC variogram model to gstat format |
| CholeskyDecomposition | Create a parameter set specifying a LU decomposition... |
| coloredBiplot.genDiag | Colored biplot for gemeralised diagonalisations Colored... |
| constructMask | Constructs a mask for a grid |
| DataFrameStack.data.frame | Create a data frame stack |
| dimnames.DataFrameStack | Return the dimnames of a DataFrameStack |
| DSpars | Create a parameter set specifying a direct sampling algorithm |
| EmpiricalStructuralFunctionSpecification-class | Empirical structural function specification |
| fit_lmc | Fit an LMC to an empirical variogram |
| getMask | Get the mask info out of a spatial data object |
| getStackElement | Set or get the i-th data frame of a data.frame stack |
| getTellus | Download the Tellus survey data set (NI) |
| gmApply | Apply Functions Over Array or DataFrameStack Margins |
| gmGaussianMethodParameters-class | parameters for Spatial Gaussian methods of any kind |
| gmGaussianSimulationAlgorithm-class | parameters for Gaussian Simulation methods |
| gmMPSParameters-class | parameters for Multiple-Point Statistics methods |
| gmNeighbourhoodSpecification-class | Neighbourhood description |
| gmSimulationAlgorithm-class | Parameter specification for a spatial simulation algorithm |
| gmSpatialDataContainer-class | General description of a spatial data container |
| gmSpatialMethodParameters-class | Parameter specification for any spatial method |
| gmSpatialModel-class | Conditional spatial model data container |
| gmTrainingImage-class | MPS training image class |
| gmUnconditionalSpatialModel-class | General description of a spatial model |
| gmValidationStrategy-class | Validation strategy description |
| GridOrNothing-class | Superclass for grid or nothing |
| gsi.calcCgram | Compute covariance matrix oout of locations |
| gsi.Cokriging | Cokriging of all sorts, internal function |
| gsi.CondTurningBands | Internal function, conditional turning bands realisations |
| gsi.DS | Workhorse function for direct sampling |
| gsi.EVario2D | Empirical variogram or covariance function in 2D |
| gsi.EVario3D | Empirical variogram or covariance function in 3D |
| gsi.gstatCokriging2compo | Reorganisation of cokriged compositions |
| gsi.orig | extract information about the original data, if available |
| gsi.produceV | Create a matrix of logcontrasts and name prefix |
| gsi.TurningBands | Internal function, unconditional turning bands realisations |
| has.missings.data.frame | Check presence of missings check presence of missings in a... |
| image_cokriged | Plot an image of gridded data |
| image.logratioVariogramAnisotropy | Plot variogram maps for anisotropic logratio variograms |
| image.mask | Image method for mask objects |
| is.anisotropySpecification | Check for any anisotropy class |
| is.isotropic | Check for anisotropy of a theoretical variogram |
| KrigingNeighbourhood | Create a parameter set of local for neighbourhood... |
| LeaveOneOut | Specify the leave-one-out strategy for validation of a... |
| length.gmCgram | Length, and number of columns or rows |
| LMCAnisCompo | Create a anisotropic model for regionalized compositions |
| logratioVariogram | Empirical logratio variogram calculation |
| logratioVariogram-acomp-method | Logratio variogram of a compositional data |
| Maf.data.frame | Generalised diagonalisations Calculate several generalized... |
| make.gmCompositionalGaussianSpatialModel | Construct a Gaussian gmSpatialModel for regionalized... |
| make.gmCompositionalMPSSpatialModel | Construct a Multi-Point gmSpatialModel for regionalized... |
| make.gmMultivariateGaussianSpatialModel | Construct a Gaussian gmSpatialModel for regionalized... |
| mean.accuracy | Mean accuracy |
| mean.spatialDecorrelationMeasure | Average measures of spatial decorrelation |
| ModelStructuralFunctionSpecification-class | Structural function model specification |
| ndirections | Number of directions of an empirical variogram |
| NfoldCrossValidation | Specify a strategy for validation of a spatial model |
| NGSAustralia | National Geochemical Survey of Australia: soil data |
| noSpatCorr.test | Test for lack of spatial correlation |
| pairsmap | Multiple maps Matrix of maps showing different combinations... |
| plot.accuracy | Plot method for accuracy curves |
| plot.gmCgram | Draw cuves for covariance/variogram models |
| plot.gmEVario | Plot empirical variograms |
| plot.logratioVariogramAnisotropy | Plot variogram lines of empirical directional logratio... |
| plot.swarmPlot | Plotting method for swarmPlot objects |
| plus-.gmCgram | Combination of gmCgram variogram structures |
| precision | Precision calculations |
| predict.genDiag | Predict method for generalised diagonalisation objects |
| predict_gmSpatialModel | Predict method for objects of class 'gmSpatialModel' |
| predict.LMCAnisCompo | Compute model variogram values Evaluate the variogram model... |
| print.mask | Print method for mask objects |
| pwlrmap | Compositional maps, pairwise logratios Matrix of maps showing... |
| SequentialSimulation | Create a parameter set specifying a gaussian sequential... |
| setCgram | Generate D-variate variogram models |
| setGridOrder | Set or get the ordering of a grid |
| setMask | Set a mask on an object |
| sortDataInGrid | Reorder data in a grid |
| spatialDecorrelation | Compute diagonalisation measures |
| spatialGridAcomp | Construct a regionalized composition / reorder compositional... |
| spatialGridRmult | Construct a regionalized multivariate data |
| spectralcolors | Spectral colors palette based on the... |
| sphTrans | Spherifying transform Compute a transformation that... |
| stackDim | Get/set name/index of (non)stacking dimensions |
| stackDim-Spatial-method | Get name/index of the stacking dimension of a Spatial object |
| sub-.DataFrameStack | Extract rows of a DataFrameStack |
| sub-.gmCgram | Subsetting of gmCgram variogram structures |
| sub-.logratioVariogramAnisotropy | Subsetting of logratioVariogram objects |
| sub-sub-.gmCgram | Subsetting of gmCgram variogram structures |
| swarmPlot | Plot a swarm of calculated output through a DataFrameStack |
| swath | Swath plots |
| TurningBands | Create a parameter set specifying a turning bands simulation... |
| unmask.data.frame | Unmask a masked object |
| validate | Validate a spatial model |
| variogram_gmSpatialModel | Variogram method for gmSpatialModel objects |
| variogramModelPlot.gmEVario | Quick plotting of empirical and theoretical variograms Quick... |
| variogramModelPlot.gstatVariogram | Quick plotting of empirical and theoretical variograms Quick... |
| variogramModelPlot.logratioVariogram | Quick plotting of empirical and theoretical logratio... |
| Windarling | Ore composition of a bench at a mine in Windarling, West... |
| write.GSLib | Write a regionalized data set in GSLIB format |
| xvErrorMeasures.data.frame | Cross-validation errror measures |
| xvErrorMeasures.default | Cross-validation errror measures |
