swd {SpherWave}R Documentation

Decomposition

Description

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

Usage

swd(sbf) 

Arguments

sbf an object of class `sbf'

Details

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

Value

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"'

References

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.

See Also

sbf, swthresh, swr.

Examples

### 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)

[Package SpherWave version 1.1.0 Index]