| %/%.fsd.fd | Subsetting a functional spatial data object |
| *.fsd.fd | Arithmetic for functional spatial data objects |
| +.fsd.fd | Arithmetic for functional spatial data objects |
| -.fsd.fd | Arithmetic for functional spatial data objects |
| /.fsd.fd | Arithmetic for functional spatial data objects |
| as.fd.fsd.fd | Converting a functional spatial data object into a functional data object |
| as.fsd.fd | Converting a functional data object into a functional spatial data object |
| center.fsd.fd | Compute the centered version of spatial functional data |
| diff.fsd.fd | Calculate the differences for a Functional Spatial Data Object |
| fsd.covariance | Estimate autocovariance operators |
| fsd.fd | Creating a functional spatial data object |
| fsd.filter | Creating a functional spatial filter |
| fsd.filter.is.unilateral | Check if functional spatial filter is unilateral |
| fsd.fourier | Compute the Fourier transform |
| fsd.fourier.inverse | Compute the Fourier inverse |
| fsd.jb.test | Perform a Jarque-Bera Test on Normality of Functional Spatial Data |
| fsd.norm | Compute the norm of functional data |
| fsd.perm | Permute the dimensions of a Functional Spatial Data Grid |
| fsd.plot.covariance | Plot the autocovariance operator of functional spatial data |
| fsd.plot.data | Plot functional spatial data |
| fsd.plot.filters | Plot functional spatial filters |
| fsd.sfarma | Simulate a spatial functional ARMA process |
| fsd.spca | Perform Spectral Principal Components Analysis on Spatial Functional Data |
| fsd.spca.cov | Calculate the Covariance of the Spectral Principal Component Scores |
| fsd.spca.filters | Calculate the Spectral Principal Components Filters Spatial Functional Data |
| fsd.spca.inverse | Reconstruct the original functional data from the filters and the score |
| fsd.spca.scores | Compute the Scores for Spatial Functional Data |
| fsd.spca.var | Calculate the Variance explained by Spectral Principal Components |
| fsd.spectral.density | Estimate the spectral density operator |
| fsd.z.plot | Plot functional data on a grid |
| Llist | a list containing the maximum lag for the filters for each variable. |
| mean.fsd.fd | Compute the mean of spatial functional data |
| mfsd | Perform Multivariate Spectral Principal Components Analysis on Spatial Functional Data. |
| mfsd.evaluation | Perform A Comparative Evaluation of Dimension Reduction: SMFPCA versus MFPCA in Multivariate Spatial Data Reconstruction |
| mfsd.nmse | Perform A Evaluation of Dimension Reduction Using NMSE and NMSE* |
| mfsd_Filter | Calculate the Multivariate Spectral Principal Components Filters Spatial Functional Data |
| mfsd_Scores | Compute the Multivariate Scores for Spatial Functional Data. |
| plot.fsd.fd | Plot functional spatial data |
| plot.fsd.filter | Plot functional spatial filters |
| plot.mfsd.fd | Plot method for mfsd.fd objects |
| qlist | a list containing tuning parameter for the estimation of the the spectral density of indian variable |
| summary.fsd.filter | Analyse functional spatial filters |
| summary.mfsd.filter | Analyse multivariate functional spatial filters |
| temp | Temperature Data in Wyoming |
| unfold | Unfold indices into a high-dimensional grid |
| X1999 | Spatial functional data of sea surface temperature (SST) data for the year 1999, derived from NOAA optimal sea surface temperature interpolation data. |
| X2000 | Spatial functional data of sea surface temperature (SST) data for the year 2000, derived from NOAA optimal sea surface temperature interpolation data. |
| X2001 | Spatial functional data of sea surface temperature (SST) data for the year 2001, derived from NOAA optimal sea surface temperature interpolation data. |
| [.fsd.fd | Subsetting a functional spatial data object |