network: Generation of Network Levels

In SpherWave: Spherical Wavelets and SW-based Spatially Adaptive Methods

Description

produces multi-resolution network by G\"ottlemann's method, modified G\"ottlemann's method or standard method.

Usage

reg.grid(x, latlon)    # for modified G\"{o}ttlemann's regular grid
red.grid(x, latlon)    # for modified G\"{o}ttlemann's reduced grid
gotreg.grid(x, latlon) # for G\"{o}ttlemann's regular grid
gotred.grid(x, latlon) # for G\"{o}ttlemann's reduced grid
hsreg.grid(x, latlon)  # for standard regular grid
hsred.grid(x, latlon)  # for standard reduced grid

Arguments

x	radius of territory in degree
latlon	grid points of observation sites in degree

Details

This function partitions the grid points of observations into networks. Each network corresponds resolution level and level 1 is the most detailed level.

Value

netlab

vector of network labels indicating level of multi-resolution.

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.

Examples

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

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

#netlab <- reg.grid(x=3, latlon)
#netlab <- red.grid(x=3, latlon)
#netlab <- gotreg.grid(x=2, latlon)
#netlab <- gotred.grid(x=2, latlon)
#netlab <- hsreg.grid(x=5, latlon)
#netlab <- hsred.grid(x=5, latlon)

SpherWave documentation built on April 14, 2017, 1:28 p.m.