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SpatialVx (version 0.6-5)

Spatial Forecast Verification

Description

Spatial forecast verification arose from verifying high-resolution forecasts, where coarser-resolution models generally are favored even when a human forecaster finds the higher-resolution model to be considerably better. Most newly proposed methods, which largely come from image analysis, computer vision, and similar, are available, with more on the way.

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Version

Install

install.packages('SpatialVx')

Monthly Downloads

265

Version

0.6-5

License

GPL (>= 2)

Maintainer

Eric Gilleland

Last Published

June 11th, 2019

Functions in SpatialVx (0.6-5)

Single Feature Properties

Forecast Quality Index

Elmore, Baldwin and Schultz Method for Field Significance for Spatial Bias Errors

Forecast Verification with Cluster Analysis: The Variation

Major and Minor Axes of a Feature

ExampleSpatialVxSet

Simulated Spatial Verification Set

FeatureMatchAnalyzer

Analyze Features of a Verification Set

Connectivity Index

Threshold-based Feature Finder

Feature-Based Contingency Table

Example Precipitation Rate Verification Set (NIMROD)

SpatialVx-package

Spatial Forecast Verification

Bearing from One Spatial Location to Another

2-d Interpolation

Loss functions for the spatial prediction comparison test (SPCT)

Force Merges in Matched Feature Objects

Raw Image Moments.

Monte Carlo Degrees of Freedom

Calculate dFSS Score Value

Temporal Block Bootstrap Keeping Locations in Space Constant

Optical Flow Verification

Centered on Square Domain Baddeley's Delta Metric

Identify Disjoint Sets of Connected Components

Merge and/or Match Identified Features Within Two Fields

SpatialVx-internal

Internal functions for the SpatialVx package

S1 Score, Anomaly Correlation

Create Composite Features

Combine Features/Matched Objects

Exponential Variogram

Exponential Variogram

Spatial Forecast Verification Methods Inter-Comparison Project (ICP) Test Cases and other example verification sets

Contiguous Rain Area

Example Verification Set

Feature Interest

calculate_FSSwind

Calculate FSSwind Score Value

Geographic Box Plot

calculate_FSSvector_from_binary_fields

Calculate FSS Values

Spatial Forecast Verification Shape Analysis

Neighborhood Verification Statistics for a Gridded Verification Set.

Quilt Plot and a Matrix Plot.

Cluster Analysis Verification

Centroid Distance Between Two Identified Objects

Simulated Forecast and Verification Fields

Test for Equal Predictive Ability on Average Over a Regularly Gridded Space

Binary Image Measures

Structure Function for Non-Gridded Spatial Fields.

Spatial Verification Sets -- SpatialVx Object

Create Surrogate Fields

structurogram.matrix

Structure Function for Gridded Fields

Localization Performance Measures

Variograms for a Gridded Verification Set

2-d Gaussian Mixture Models Verification

Rigid Transformation

Some Common Traditional Forecast Verification Statistics.

Intensity Scale (IS) Verification

Apply Traditional Forecast Verification After Wavelet Denoising

Feature-based Analysis of a Field (Image)

Create Several Graphics for List Objects Returned from hoods2d

Apply a Threshold to a Field

Various Verification Statistics on Possibly Neighborhood-Smoothed Fields.

Practically Perfect Hindcast Neighborhood Verification Method

Upscaling Neighborhood Verification on a 2-d Verification Set

Field Significance Method of Elmore et al. (2006)

Variography Score

Spatial Prediction Comparison Test

High-Resolution Gridded Forecast Verification Using Discrete Wavelet Decomposition

Binary Location Metric Proposed in Zhu et al. (2011)

Minimum Boundary Separation Feature Matching