Cover image
Normal view MARC view ISBD view

Two-dimensional kernel smoothing: Using the R package "smoothie" / by Eric Gilleland

by Gilleland, Eric; National Center for Atmospheric Research (U.S.)Joint Numerical Testbed, -- Research Applications Laboratory, .
Series: NCAR technical note ; NCAR/TN-502+STR. Publisher: Boulder, Colo. : National Center for Atmospheric Research, 2013ISSN: 2153-2397; 2153-2400.Subject(s): Kernel smoothing | Neighborhood forecast verification | Two-dimensional field smoothing | Image smoothing | Fast Fourier transform | Convolution theorem | R software packageOnline resources: Click here to access online Summary: Applying a kernel smoother to a two-dimensional field can be a laborious and computationally expensive process if carried out in the most obvious fashion (applying a double loop). One might consider the alternative of stacking a location matrix and applying the kernel smoother in a more efficient way (e.g., through the R function aggregate). However, for large grids this may not be practical or even possible. The methods have the advantage of being able to handle missing values and edges (with fewer neighbors) directly, but if these are not pivotal concerns, the convolution theorem along with the fast Fourier transform (FFT) provides a very speedy alternative. The R package smoothie provides functionality for smoothing a two-dimensional field (or image) using the convolution theorem and FFT, and is used extensively in the spatial weather forecast verification package, SpatialVx.
Item type Location Call number Copy Status Date due
REPORT REPORT Mesa Lab 03704 (Browse shelf) 1 Available

2013

Applying a kernel smoother to a two-dimensional field can be a laborious and computationally expensive process if carried out in the most obvious fashion (applying a double loop). One might consider the alternative of stacking a location matrix and applying the kernel smoother in a more efficient way (e.g., through the R function aggregate). However, for large grids this may not be practical or even possible. The methods have the advantage of being able to handle missing values and edges (with fewer neighbors) directly, but if these are not pivotal concerns, the convolution theorem along with the fast Fourier transform (FFT) provides a very speedy alternative. The R package smoothie provides functionality for smoothing a two-dimensional field (or image) using the convolution theorem and FFT, and is used extensively in the spatial weather forecast verification package, SpatialVx.

Any questions? Ask a Librarian.

Not finding what you are looking for? Request-It - InterLibrary Loan.

Languages: