rcontrib

A measure of how correlated a variable is with those in a set is given by the 
 square root of the sum of squares of the correlation coefficients between the 
 variables and the other variables in the set (Cumming and Wooff, 2007). Here, the partial 
 correlation between the subset of the variables listed in <code>response</code> that 
 are not listed in <code>include</code> is calculated from the partial correlation matrix 
 for the subset, adjusting for those variables in <code>include</code>. This is useful 
 for manually deciding which of the variables not in <code>include</code> should next be 
 added to it.

manip

data

Assists in the plotting and functional smoothing of traits
measured over time and the extraction of features from these traits,
implementing the SET (Smoothing and Extraction of Traits) method
described in Brien et al. (2020) Plant Methods, 16. Smoothing of
growth trends for individual plants using natural cubic smoothing
splines or P-splines is available for removing transient effects and
segmented smoothing is available to deal with discontinuities in
growth trends. There are graphical tools for assessing the adequacy
of trait smoothing, both when using this and other packages, such as
those that fit nonlinear growth models. A range of per-unit (plant,
pot, plot) growth traits or features can be extracted from the
data, including single time points, interval growth rates and other
growth statistics, such as maximum growth or days to maximum growth.
The package also has tools adapted to inputting data from
high-throughput phenotyping facilities, such from a Lemna-Tec
Scananalyzer 3D (see <https://www.youtube.com/watch?v=MRAF_mAEa7E/>
for more information). The package 'growthPheno' can also be
installed from <http://chris.brien.name/rpackages/>.

Chris Brien

growthPheno

Functional Analysis of Phenotypic Growth Data to Smooth and
Extract Traits

rcontrib function

<dl> <dt>obj</dt>
<dd>A <code><a href="/link/data.frame?package=growthPheno&version=2.1.23" data-mini-rdoc="growthPheno::data.frame">data.frame</a></code> containing the columns of variables from which the 
 correlation measure is to be calculated.</dd> <dt>...</dt>
<dd>allows passing of arguments to other functions</dd></dl>

Arguments

Author

Computes a measure of how correlated each variable in a set is with the other variable, 
       conditional on a nominated subset of them — rcontrib

<dl>

 <dt>obj</dt>
<dd>A <code><a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a></code> containing the columns of variables from which the 
 correlation measure is to be calculated.</dd>

 <dt>...</dt>
<dd>allows passing of arguments to other functions</dd>

</dl>

rcontrib: Computes a measure of how correlated each variable in a set is with the other variable, conditional on a nominated subset of them

Description

Usage

Value

Arguments

Author

Details

References

See Also