ezCor {ez} | R Documentation |
This function provides simultaneous visualization of a correlation matrix, scatter-plot with linear fits, and univariate density plots for multiple variables.
ezCor( data , r_size_lims = c(10,30) , point_alpha = .5 , density_height = 1 , density_adjust = 1 , density_colour = 'white' , label_size = 10 , label_colour = 'black' , label_alpha = .5 , lm_colour = 'red' , ci_colour = 'green' , ci_alpha = .5 )
data |
Data frame containing named columns of data only. |
r_size_lims |
Minimum and maximum size of the text reporting the correlation coefficients. Minimum is mapped to coefficients of 0 and maximum is mapped to coefficients of 1, with the mapping proportional to r^2. |
point_alpha |
Transparency of the data points (1 = opaque). |
density_adjust |
Adjusts the bandwidth of the univariate density estimator. See "adjust" parameter in density
|
density_height |
Proportion of the facet height taken up by the density plots. |
density_colour |
Colour of the density plot. |
label_size |
Size of the variable labels on the diagonal. |
label_colour |
Colour of the variable labels on the diagonal. |
label_alpha |
Transparency of the variable labels on the diagonal (1 = opaque). |
lm_colour |
Colour of the fitted line. |
ci_colour |
Colour of the confidence interval surrounding the fitted line. |
ci_alpha |
Transparency of the confidence interval surrounding the fitted line (1 = opaque). |
A ggplot2 object.
Michael A. Lawrence Mike.Lawrence@dal.ca
ezANOVA
, ezPerm
, ezPlot
, ezStats
######## # Set up some fake data ######## library(MASS) N=100 #first pair of variables variance1=1 variance2=2 mean1=10 mean2=20 rho = .8 Sigma=matrix(c(variance1,sqrt(variance1*variance2)*rho,sqrt(variance1*variance2)*rho,variance2),2,2) pair1=mvrnorm(N,c(mean1,mean2),Sigma,empirical=TRUE) #second pair of variables variance1=10 variance2=20 mean1=100 mean2=200 rho = -.4 Sigma=matrix(c(variance1,sqrt(variance1*variance2)*rho,sqrt(variance1*variance2)*rho,variance2),2,2) pair2=mvrnorm(N,c(mean1,mean2),Sigma,empirical=TRUE) my_data=data.frame(cbind(pair1,pair2)) ######## # Now plot ######## p = ezCor( data = my_data ) print(p) #you can modify the default colours of the correlation coefficients as follows p = p + scale_colour_manual(values = c('red','blue')) print(p) #see the following for alternatives: # http://had.co.nz/ggplot2/scale_manual.html # http://had.co.nz/ggplot2/scale_hue.html # http://had.co.nz/ggplot2/scale_brewer.html