pcdiags.plt {pcurve} | R Documentation |
A menu of 12 plots for diagnosis of results from principal curve
analysis, pcurve
pcdiags.plt(zz, xx, pch = 1, graphics = TRUE)
zz |
an object of class principal curve, being the value of the
funtion |
xx |
data.frame or matrix of explanatory (environmental) variables to be used in constrained pcs. |
pch |
symbol to be used in plots. |
graphics |
a logical argument of |
Produces a menu of 12 (or thirteen if xx is not missing) options. Once a selection is made, return to the menu by left-mouse clicking on the plot.
0. Exit
1. Residuals plots for each variable on the PC (by the internal function
pcres1.plt
)
2. Absolute residuals plot for each variable on the PC (by the internal
function pcres2.plt
)
3. QQ normal residuals plot for each variable (by the internal function
pcqqnorm.plt
)
4. QQ chi-squared quantile residuals plot (by the internal function
pcchisq.plt
)
5. Response plot and residual plot for each variable (by the internal
function pcresid.plt
)
6. Differenced locations: Plot of distances between consecutive
locations on the PC (by the internal function pcfinder.plt
)
7. Response plots for each variable along the PC (by the internal
function pcresp.plt
)
8. Flip plots: Plot of the PC projected onto a bi-plot of the first two
principal coordinates, showing fitted locations of the variables on the
PC. Left-mouse click to scroll through biplots of other principal
coordinate combinations. (Right-mouse-click to return to the menu)
(Using the internal function pcflip.plt
)
9. Fix curve: a utility to break the curve in up to two places (by left
mouse-clicks), re-order the segments and rerun the PC analysis with a
new start. (using the internal function finder
)
10. Scatterplots of Eclidean and Bray-Curtis distances against the
PC. (using the internal function pcdists.plt
)
11. Histograms of Eclidean and Bray-Curtis distances against the
PC. (using the internal function pchist.plt
)
12. A toggle to use Case numbers or symbols in plots
13. Env. vars. vs Gradient: if xx is not missing, plots of distance
along the PC and explanatory variables (using the internal function pcenv.plt
)
Produces plots
R port by Chris Walsh cwalsh@unimelb.edu.au from S+ library by Glenn De'ath g.death@aims.gov.au.
De'ath, G. 1999 Principal Curves: a new technique for indirect and direct gradient analysis. Ecology 80, 2237–2253.