Function generates a principal component plot for trajectories
# S3 method for trajectory.analysis
plot(x, ...)If an object is assigned, it will return:
Principal component analysis performed using prcomp.
Principal component scores for all data.
Trajectory analysis passed on.
pca Observed trajectories projected onto principal components.
plot object (from trajectory.analysis)
other arguments passed to plot (helpful to employ
different colors or symbols for different groups). See
plot.default and par
Michael Collyer
The function calculates and plots principal components of fitted values from
lm.rrpp that are passed onto trajectory.analysis,
and projects
data onto them. This function is a set.up, and add.trajectories
is needed to
add trajectories to the plot. By having two stages of control, the plotting
functions are more
flexible. This function also returns plotting information that can be
valuable for making
individualized plots, if add.trajectories is not preferred.
Adams, D. C., and M. M. Cerney. 2007. Quantifying biomechanical motion using Procrustes motion analysis. J. Biomech. 40:437-444.
Adams, D. C., and M. L. Collyer. 2007. The analysis of character divergence along environmental gradients and other covariates. Evolution 61:510-515.
Adams, D. C., and M. L. Collyer. 2009. A general framework for the analysis of phenotypic trajectories in evolutionary studies. Evolution 63:1143-1154.
Collyer, M. L., and D. C. Adams. 2007. Analysis of two-state multivariate phenotypic change in ecological studies. Ecology 88:683-692.
Collyer, M. L., and D. C. Adams. 2013. Phenotypic trajectory analysis: comparison of shape change patterns in evolution and ecology. Hystrix 24: 75-83.
Collyer, M.L., D.J. Sekora, and D.C. Adams. 2015. A method for analysis of phenotypic change for phenotypes described by high-dimensional data. Heredity. 115:357-365.
plot.default and par
# See trajectory.analysis help file for examples
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