sbf {SpherWave} | R Documentation |
This function performs extrapolation with multi-sale SBF's.
sbf(obs, latlon, netlab, eta, method, approx=FALSE, grid.size=c(50, 100), lambda=NULL, p0=0, latlim=NULL, lonlim=NULL)
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 west of the Prime (Greenwich) Meridian. East/West are represented by +/- sign. |
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, ..., L, resolution levels p0+1, ..., L will be included for extrapolation. |
latlim |
range of latitudes in degree |
lonlim |
range of longitudes in degree |
This function performs extrapolation with multi-sale SBF's.
An object of class `sbf'. 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 |
density |
density on observation's locations |
latlim |
range of latitudes in degree |
lonlim |
range of longitudes in degree |
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.
### 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)