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Data · dataset · 2026

Two-dimensional kernel smoothing: Using the R package smoothie

Listed in National Center for Atmospheric Research

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).

Description

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, Spatial Vx.

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Provenance · 1 source records, 9 field assertions
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National Center for Atmospheric Research9bf07189-4ac6-4da7-a4d2-602e9042a5eb11 d agoJSON v1
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concepts[field].local:field:mathematics-statisticsmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[modality].local:modality:imageenrichment · data ucar edukeyword-concept-rules@1.0.0title+description (75%)
created_datesource · data ucar educonnector:data_ucar_edu@1.0.0
descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
publication_datesource · data ucar educonnector:data_ucar_edu@1.0.0
titlesource · data ucar educonnector:data_ucar_edu@1.0.0/title
updated_datesource · data ucar educonnector:data_ucar_edu@1.0.0