CRAN/E | SailoR

SailoR

An Extension of the Taylor Diagram to Two-Dimensional Vector Data

Installation

About

A new diagram for the verification of vector variables (wind, current, etc) generated by multiple models against a set of observations is presented in this package. It has been designed as a generalization of the Taylor diagram to two dimensional quantities. It is based on the analysis of the two-dimensional structure of the mean squared error matrix between model and observations. The matrix is divided into the part corresponding to the relative rotation and the bias of the empirical orthogonal functions of the data. The full set of diagnostics produced by the analysis of the errors between model and observational vector datasets comprises the errors in the means, the analysis of the total variance of both datasets, the rotation matrix corresponding to the principal components in observation and model, the angle of rotation of model-derived empirical orthogonal functions respect to the ones from observations, the standard deviation of model and observations, the root mean squared error between both datasets and the squared two-dimensional correlation coefficient. See the output of function UVError() in this package.

Citation SailoR citation info

Key Metrics

Version 1.2
R ≥ 3.5.0
Published 2020-09-23 1169 days ago
Needs compilation? no
License GPL-3
CRAN checks SailoR results

Downloads

Last 24 hours 0 -100%
Last 7 days 38 +12%
Last 30 days 160 +1%
Last 90 days 461 -0%
Last 365 days 2.056 -47%

Maintainer

Maintainer

Santos J. González-Rojí

santosjose.gonzalez@ehu.eus

Authors

Jon Sáenz

aut / cph

Sheila Carreno-Madinabeitia

aut / cph

Santos J. González-Rojí

aut / cre / cph

Ganix Esnaola

ctb / cph

Gabriel Ibarra-Berastegi

ctb / cph

Alain Ulazia

ctb / cph

Material

NEWS
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

SailoR archive

Depends

R ≥ 3.5.0