dplot {Prize} | R Documentation |
Computing and plotting the distance between individuals and group judgement. Distances are computed using classical multidimensional scaling (MDS) approach.
dplot(srcfile, fontsize = 15, xcex = 10, ycex = 10, lcex = 5, hjust = 0.5, vjust = 1, xlab = "Coordinate 1", ylab = "Coordinate 2", main = NULL)
srcfile |
a numeric matrix of individual and group priorities. |
fontsize |
the font size of the plot title, and x and y axis labels. The default value is 15. |
xcex,ycex |
the font size of the x and y axis, respectively. The default values is 10. |
lcex |
the font size of point labels in dplot |
hjust,vjust |
the horizontal and vertical justification of point labels, respectively. |
xlab,ylab |
the label of the x and y axis, respectively. |
main |
the plot title |
An object created by 'ggplot'.
Daryanaz Dargahi
J.C. Gower. Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika, 53(3/4):pp. 325-338, 1966.
mat <- matrix(nrow = 5, ncol = 4, data = NA) rownames(mat) <- c('Ind1','Ind2','Ind3', 'Ind4' ,'Group judgement') colnames(mat) <- c('Tumor_expression','Normal_expression','Frequency','Epitopes') mat[1,] <- c(0.4915181, 0.3058879, 0.12487821, 0.07771583) mat[2,] <- c(0.3060687, 0.4949012, 0.12868606, 0.07034399) mat[3,] <- c(0.4627138, 0.3271881, 0.13574662, 0.07435149) mat[4,] <- c(0.6208484, 0.2414021, 0.07368481, 0.06406465) mat[5,] <- c(0.4697298, 0.3406738, 0.11600194, 0.07359445) dplot(mat, xlab = 'Coordinate 1', ylab = 'Coordinate 2', main = 'Distance plot')