PCMPlotTraitData2D

tree

numeric parameters passed as arguments size and alpha to <code>geom_point</code>.
Default: sizePoints = 2, alphaPoints = 1.

sizePoints, alphaPoints

a vector of tip-numbers to label (NULL by default)

labeledTips

passed to <code>geom_text</code> to specify the size of tip-labels for the trait-points.

sizeLabels

a numeric vector of two elements (default: c(0,0)), passed as
arguments nudge_x and nudge_y of <code>geom_text</code>.

nudgeLabels

palette

logical indicating if the size and the transparency of the points
should reflect the distance from the present (points that are farther away in time with
respect to the present moment, i.e. closer to the root of the tree, are displayed smaller
and more transparent.). By default this is set to <code>!is.ultrametric(tree)</code>.

scaleSizeWithTime

a number or a numeric vector controlling the creation of different facets
corresponding to different time intervals when the tree is non-ultrametric. If a single number,
it will be interpreted as an integer specifying the number of facets, each facets corresponding to
an equal interval of time. If a numeric vector, it will be used to specify the cut-points for
each interval. Default: <code>if(is.ultrametric(tree) || scaleSizeWithTime) 1L else 3</code>.

numTimeFacets

integers specifying how the time facets should
be layed out. Default: <code>nrowTimeFacets = 1L, ncolTimeFacets = numTimeFacets</code>.

nrowTimeFacets, ncolTimeFacets

Scatter plot of 2-dimensional data

Phylogenetic comparative methods represent models of continuous trait
data associated with the tips of a phylogenetic tree. Examples of such models
are Gaussian continuous time branching stochastic processes such as Brownian
motion (BM) and Ornstein-Uhlenbeck (OU) processes, which regard the data at the
tips of the tree as an observed (final) state of a Markov process starting from
an initial state at the root and evolving along the branches of the tree. The
PCMBase R package provides a general framework for manipulating such models.
This framework consists of an application programming interface for specifying
data and model parameters, and efficient algorithms for simulating trait evolution
under a model and calculating the likelihood of model parameters for an assumed
model and trait data. The package implements a growing collection of models,
which currently includes BM, OU, BM/OU with jumps, two-speed OU as well as mixed
Gaussian models, in which different types of the above models can be associated
with different branches of the tree. The PCMBase package is limited to
trait-simulation and likelihood calculation of (mixed) Gaussian phylogenetic
models. The PCMFit package provides functionality for ML and Bayesian fit of
these models to tree and trait data. The package web-site
<https://venelin.github.io/PCMBase/>
provides access to the documentation and other resources.

PCMPlotTraitData2D: Scatter plot of 2-dimensional data

Description

Usage

Arguments

Value