# plot.anacor: Plots for anacor solution In anacor: Simple and Canonical Correspondence Analysis

## Description

These functions produce various plots for objects of class `"anacor"`

## Usage

 ```1 2 3 4 5 6``` ```## S3 method for class 'anacor' plot(x, plot.type = "jointplot", plot.dim = c(1,2), col.row = "cadetblue", col.column = "coral1", catlabels = list(label.row = TRUE, label.col = TRUE, col.row = "cadetblue", col.column = "coral1", cex = 0.8, pos = 3), legpos = "top", arrows = c(FALSE, FALSE), conf = 0.95, wlines = 0, asp = 1, pch = 20, xlab, ylab, main, type, xlim, ylim, cex.axis2, ...) ```

## Arguments

 `x` Object of class `"anacor"` `plot.type` Type of plot to be produced (details see below): 2-D and 3-D for `"jointplot"`, `"rowplot"`, and `"colplot"`; 2-D for `"regplot"`, `"graphplot"`, `"benzplot"`, `"transplot"`, and `"orddiag"`. `plot.dim` Vector of length 2 with Dimensions to be plotted. For `"regplot"` a single value should be provided, for `"transplot"` more than two dimensions are allowed, and for `"benzplot"` this argument is ignored. `col.row` Color row categories `col.column` Color column categories `catlabels` Various parameter settings for labels `legpos` Position of the legend (for `"transplot"` only) `conf` Ellipsoid confidence level for `"jointplot"`, `"rowplot"`, and `"colplot"`, assuming that the ellipse where computed in `anacor()`. If `NULL`, no ellipsoids are drawn. `arrows` Whether arrows from the origin to the row scores (first element) or column scores (second element) should be drawn. `wlines` For `"graphplot"` only: If 0, all lines are of the same thickness. For values > 0 line thickness indicates the strength of the pull `asp` Aspect ratio. `pch` Symbol for plotting points. `xlab` Label x-axis. `ylab` Label y-axis. `xlim` Scale x-axis. `ylim` Scale y-axis. `main` Plot title. `type` Whether points, lines or both should be plotted; for `"regplot"` and `"transplot"` only. `cex.axis2` For `"regplot"` only. The magnification to be used for the category labels in the scaled solution relative to the current setting of cex. `...` Additional graphical parameters.

## Details

The following plot types are provided: `"jointplot"` plots row and column scores into the same device, `"rowplot"` and `"colplot"` plot the row scores and column scores, respectively, in separate devices. For these types of plots 3-dimensional versions are provided. The graph plot is an unlabeled version of the joint plot where the points are connected by lines. Options are provided (`wlines`) to steer the line thickness indicating the connection strength.

The regression plot (`"regplot"`) provides two plots. First, the unscaled solution is plotted. A frequency grid for the row categories (x-axis) and column categories (y-axis) is produced. The regression line is based on the category weighted means of the relative frequencies: the blue line on the column-wise means on the x-axis and the column category on the y-axis, the red line is based on the row categories on the x-axis and the row-wise means on the y-axis. In a second device the scaled solution is plotted. The frequency grid is determined by the row scores (x-axis) and the column scores(y-axis). Now, instead of the row/column categories, the column scores (black line y-axis) and the row scores (red line x-axis) are used.

The transformation plot (`"transplot"`) plots the row/column categories against the row/column scores. The Benzecri plot (`"benzplot"`) plots the observed distances against the fitted distances. It is assumed that the CA result is Benzecri scaled. The ordination diagram (`"orddiag"`) for CCA produces a joint plot and includes the column and row covariates based on intraset correlations.

## Author(s)

Jan de Leeuw, Patrick Mair

## References

De Leeuw, J. and Mair, P. (2009). Simple and Canonical Correspondence Analysis Using the R Package anacor. Journal of Statistical Software, 31(5), 1-18. http://www.jstatsoft.org/v31/i05/

`anacor`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31``` ```## symmetric map data(tocher) res <- anacor(tocher) plot(res, conf = NULL, main = "Symmetric Map") ## simple CA on Tocher data, asymmetric coordinates res <- anacor(tocher, scaling = c("standard", "Benzecri")) res ## Regression plots using Glass data data(glass) res <- anacor(glass) plot(res, plot.type = "regplot", xlab = "fathers occupation", ylab = "sons occupation") ## Benzecri Plots for bitterling data data(bitterling) res1 <- anacor(bitterling, ndim = 2, scaling = c("Benzecri", "Benzecri")) res2 <- anacor(bitterling, ndim = 5, scaling = c("Benzecri", "Benzecri")) res2 plot(res1, plot.type = "benzplot", main = "Benzecri Distances (2D)") plot(res2, plot.type = "benzplot", main = "Benzecri Distances (5D)") ## Column score plot,transformation plot, and ordination diagram for canonical CA data(maxwell) res <- anacor(maxwell\$table, row.covariates = maxwell\$row.covariates, scaling = c("Goodman", "Goodman")) res plot(res, plot.type = "colplot", xlim = c(-1.5,1), conf = NULL) plot(res, plot.type = "transplot", legpos = "topright") plot(res, plot.type = "orddiag") ```

anacor documentation built on May 2, 2019, 9:33 a.m.