themes

theme_metan

theme_metan_minimal

transparent_color

alpha_color

Control the grid lines in plot. Defaults to <code>"both"</code> (x and
y major grids). Allows also <code>grid = "x"</code> for grids in x axis only,
<code>grid = "y"</code> for grid in y axis only, or <code>grid = "none"</code> for no
grids.

grid

col.grid

The color for the panel background.

color.background

color

An alpha value for transparency (0 &lt; alpha &lt; 1).

alpha

<ul>
<li><code>theme_metan()</code>: Theme with a gray background and major grids.</li>
<li><code>theme_metan_minimal()</code>: A minimalistic theme with half-open frame, white
background, and no grid. For more details see <code><a rd-options="ggplot2" href="/link/theme?package=metan&version=1.10.0&to=ggplot2" data-mini-rdoc="ggplot2::theme">theme</a></code>.</li>
<li><code>transparent_color()</code>: A helper function to return a transparent color
with Hex value of "#000000FF"</li>
<li><code>alpha_color()</code>: Return a semi-transparent color based on a color name
and an alpha value. For more details see <code><a rd-options="grDevices" href="/link/colors?package=metan&version=1.10.0&to=grDevices" data-mini-rdoc="grDevices::colors">colors</a></code>.</li>
</ul>

Performs stability analysis of multi-environment
trial data using parametric and non-parametric methods. Parametric
methods includes Additive Main Effects and Multiplicative Interaction
(AMMI) analysis by Gauch (2013) <doi:10.2135/cropsci2013.04.0241>,
Ecovalence by Wricke (1965), Genotype plus Genotype-Environment (GGE)
biplot analysis by Yan & Kang (2003) <doi:10.1201/9781420040371>,
geometric adaptability index by Mohammadi & Amri (2008)
<doi:10.1007/s10681-007-9600-6>, joint regression analysis by Eberhart
& Russel (1966) <doi:10.2135/cropsci1966.0011183X000600010011x>,
genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's
(2004) method <doi:10.12702/1984-7033.v04n01a02>, power law residuals
(POLAR) statistics by Doring et al. (2015)
<doi:10.1016/j.fcr.2015.08.005>, scale-adjusted coefficient of
variation by Doring & Reckling (2018) <doi:10.1016/j.eja.2018.06.007>,
stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>,
weighted average of absolute scores by Olivoto et al. (2019a)
<doi:10.2134/agronj2019.03.0220>, and multi-trait stability index by
Olivoto et al. (2019b) <doi:10.2134/agronj2019.03.0221>.
Non-parametric methods includes superiority index by Lin & Binns
(1988) <doi:10.4141/cjps88-018>, nonparametric measures of phenotypic
stability by Huehn (1990)
<https://link.springer.com/article/10.1007/BF00024241>, TOP third
statistic by Fox et al. (1990) <doi:10.1007/BF00040364>. Functions for
computing biometrical analysis such as path analysis, canonical
correlation, partial correlation, clustering analysis, and tools for
inspecting, manipulating, summarizing and plotting typical
multi-environment trial data are also provided.

Tiago Olivoto

metan

Multi Environment Trials Analysis

themes function

<ul>
<li><code>theme_metan()</code>: Theme with a gray background and major grids.</li>
<li><code>theme_metan_minimal()</code>: A minimalistic theme with half-open frame, white
background, and no grid. For more details see <code><a rd-options='ggplot2' href='theme'>theme</a></code>.</li>
<li><code>transparent_color()</code>: A helper function to return a transparent color
with Hex value of "#000000FF"</li>
<li><code>alpha_color()</code>: Return a semi-transparent color based on a color name
and an alpha value. For more details see <code><a rd-options='grDevices' href='colors'>colors</a></code>.</li>
</ul>

themes: Personalized theme for ggplot2-based graphics

Description

Usage

Arguments