swd: Decomposition
In SeoncheolPark/SphereWaveu:

Description Usage Arguments Details Value References See Also Examples

This function performs decomposition with multi-sale SBF's.

swd(sbf)

sbf

an object of class ‘sbf’

This function performs decomposition with multi-sale SBF's.

An object of class spherical wavelet decomposition(‘swd’). This object is a list with the following components.

`obs`	observations
`latlon`	grid points of observation sites in degree
`netlab`	vector of labels representing sub-networks
`eta`	bandwidth parameters for Poisson kernel
`method`	extrapolation methods, ‘"ls"’ or ‘"pls"’
`approx`	if TRUE, approximation is used.
`grid.size`	grid size (latitude, longitude) of extrapolation site
`lambda`	smoothing parameter for penalized least squares method
`p0`	starting level for extrapolation. Resolution levels p0+1, …, L is used for extrapolation.
`gridlon`	longitudes of extrapolation sites in degree
`gridlat`	latitudes of extrapolation sites in degree
`nlevels`	the number of multi-resolution levels
`coeff`	interpolation coefficients
`field`	extrapolation on grid.size
`density1`	density of SBF
`latlim`	range of latitudes in degree
`lonlim`	range of longitudes in degree
`global`	List of successively smoothed data
`density`	density of SW coefficients
`detail`	List of details at different resolution levels
`swcoeff`	SW coefficients
`thresh.info`	‘"None"’

Oh, H-S. and Li, T-H. (2004) Estimation of global temperature fields from scattered observations by a spherical-wavelet-based spatially adaptive method. Journal of the Royal Statistical Society Ser. B, 66, 221–238.

sbf, swthresh, swr.

### Observations of year 1967
#data(temperature)
#names(temperature)

# Temperatures on 939 weather stations of year 1967    
#temp67 <- temperature$obs[temperature$year == 1967] 
# Locations of 939 weather stations    
#latlon <- temperature$latlon[temperature$year == 1967, ]

### Network design by BUD
#data(netlab)

### Bandwidth for Poisson kernel
#eta <- c(0.961, 0.923, 0.852, 0.723, 0.506)

### SBF representation of the observations by pls
#out.pls <- sbf(obs=temp67, latlon=latlon, netlab=netlab, eta=eta, 
#    method="pls", grid.size=c(50, 100), lambda=0.89)

### Decomposition
#out.dpls <- swd(out.pls)