# plot.aspect: Plot method for aspect solutions In aspect: A General Framework for Multivariate Analysis with Optimal Scaling

## Description

This method provides regression plots and transformation plots for objects of class `"aspect"`, i.e. solutions of `corAspect` and `lineals`

## Usage

 ```1 2``` ```## S3 method for class 'aspect' plot(x, plot.type, plot.var = c(1,2), xlab, ylab, main, type, ...) ```

## Arguments

 `x` Object of class `"aspect"`. `plot.type` Type of plot to be produced (details see below): `"regplot"`, `"transplot"`. `plot.var` For `plot.type = "regplot"` only. Vector of length 2 with variables to be plotted. Either variable names of column number. `xlab` Label x-axis. `ylab` Label y-axis. `main` Plot title. `type` Whether points, lines or both should be plotted. `...` Additional graphical parameters.

## Details

The regression plot (`"regplot"`) provides two plots. First, the unscaled solution is plotted. A frequency grid for the categories of the first variable (var1; x-axis) and the categories of the second variable (var2; y-axis) is produced. The regression line is based on the category weighted means of the relative frequencies: the blue line on the var1 means on the x-axis and the var2 categories on the y-axis, the red line is based on the var1 categories on the x-axis and the var2 means on the y-axis. In a second device the scaled solution is plotted. The frequency grid is determined by the var1 scores (x-axis) and the var2 scores(y-axis). Now, instead of the var1/var2 categories, the var1 scores (blue line y-axis) and the row scores (red line x-axis) are used.

The transformation plot (`"transplot"`) plots the raw categories against the computed scores.

`lineals`, `corAspect`
 ```1 2 3 4 5``` ```##Regression plots using galo data data(galo) res <- lineals(galo[,1:4]) #plot(res, plot.type = "regplot", plot.var = c("advice","SES")) #plot(res, plot.type = "transplot") ```