Plot Function for RRPP
Function generates a principal component plot for trajectories
## S3 method for class 'trajectory.analysis' plot(x, ...)
x: plot object (from trajectory.analysis)...: other arguments passed to plot (helpful to employ different colors or symbols for different groups). See plot.default and parIf an object is assigned, it will return: - pca: Principal component analysis performed using prcomp.
pc.points: Principal component scores for all data.
trajectory.analysis: Trajectory analysis passed on.
trajectories: pca Observed trajectories projected onto principal components.
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.
# See trajectory.analysis help file for examples
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
Michael Collyer