Andrews plot for multivariate data.
h = nan_andrewsplot(X) h = nan_andrewsplot(X,groups) h = nan_andrewsplot(X,groups,quant) h = nan_andrewsplot(X,groups,quant,stdize)
Rows of X correspond to observations, columns to variables.
plots the data in different groups with different colors, must be a numeric array or character matrix,
if it is not empty it plots only the median and the quant and (1-quant) quantiles of f(t) at each value of t. This is useful if X contains many observations.
do nothing
scales each column of X to have zero mean and unit standard deviation before making the plot.
creates an Andrews plot from the principal component scores of X, in order of decreasing eigenvalue.
uses the standardized principal component scores.
handles to the line objects
nan_andrewsplot(X) creates an Andrews plot of the multivariate data in the matrix X.
An Andrews plot is a tool for visualizing high dimensional data, where each observation is represented by a function, f(t), of a continuous dummy variable, t, over the interval [0,1]. f(t) is defined for the i-th observation in X as
f(t) = X(i,1)/sqrt(2) + X(i,2)*sin(2*pi*t) + X(i,3)*cos(2*pi*t) + ...
andrewsplot treats NaNs in X as missing values, and ignores the corresponding rows.
// make a grouped plot of the raw data loadmatfile("demos/data/iris.mat"); nan_andrewsplot(meas,species); // plot only the median and quartiles of each group nan_andrewsplot(meas,species,.25);
[1] Gnanadesikan, R. (1977) Methods for Statistical Dara Analysis of Multivariate Observations, Wiley.