Optimal kernel widths output by
ma are employed to
recompute the weighted joint distribution for two variables in
a data set, and a contour plot for this distribution is drawn.
an n x m data frame with m > 1.
the column index of the independent variable
the column index of the dependent variable
A data set of two variables is extracted from the user's data set and a
full distribution is calculated
using weighted marginal and joint likelihoods. The optimal kernel sizes and
weighting are first computed via a call to
An n x n distribution of weighted likelihoods is returned.
The data set must contain at least 2 columns.
Ben Murrell, Dan Murrell & Hugh Murrell.
Discovering general multidimensional associations, http://arxiv.org/abs/1303.1828
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