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SpherWave (version 1.2.0)

sbf: Extrapolation with Multi-sale SBF's

Description

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

Usage

sbf(obs, latlon, netlab, eta, method, approx=FALSE,
    grid.size=c(50, 100), lambda=NULL, p0=0, latlim=NULL, 
    lonlim=NULL)

Arguments

obs
observations
latlon
grid points of observation sites in degree. Latitude is the angular distance in degrees of a point north or south of the Equator. North/South are represented by +/- sign. Longitude is the angular distance in degrees of a point east or wes
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
specifies starting level for extrapolation. Among resolution levels $1, \ldots, L$, resolution levels $p0+1, \ldots, L$ will be included for extrapolation.
latlim
range of latitudes in degree
lonlim
range of longitudes in degree

Value

  • An object of class `sbf'. This object is a list with the following components.
  • obsobservations
  • latlongrid points of observation sites in degree
  • netlabvector of labels representing sub-networks
  • etabandwidth parameters for Poisson kernel
  • methodextrapolation methods, `"ls"' or `"pls"'
  • approxif TRUE, approximation is used.
  • grid.sizegrid size (latitude, longitude) of extrapolation site
  • lambdasmoothing parameter for penalized least squares method
  • p0starting level for extrapolation. Resolution levels $p0+1, \ldots, L$ is used for extrapolation.
  • gridlonlongitudes of extrapolation sites in degree
  • gridlatlatitudes of extrapolation sites in degree
  • nlevelsthe number of multi-resolution levels
  • coeffinterpolation coefficients
  • fieldextrapolation on grid.size
  • densitydensity on observation's locations
  • latlimrange of latitudes in degree
  • lonlimrange of longitudes in degree

Details

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

References

Oh, H-S. (1999) Spherical wavelets and their statistical analysis with applications to meteorological data. Ph.D. Thesis, Department of Statistics, Texas A&M University, College Station. Li, T-H. (1999) Multiscale representation and analysis of spherical data by spherical wavelets. SIAM Journal on Scientific Computing, 21, 924--953. 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

swd, swthresh, swr.

Examples

Run this code
### 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)

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