u copularnd ( Gaussian ,-0.8,1000) figure scatterhist (u (:,1),u (:,2)) The histograms show that the data in each column of. Create a scatterhist plot to visualize the random numbers generated from the copula.

P(ii) = plot(xii,fii,'LineWidth',1.1,'Marker','.','MarkerSize',12) Īlternatively, you could just plot each first, figure, hold onĪnd then change the properties of each line later with p(1).foo (see here).įor example, one at a time: p(1). Use copularnd to generate 1000 correlated random numbers with a correlation coefficient equal to 0.8, using a Gaussian copula. Explore thousands of free applications from the Wolfram Demonstrations Project and other open-source resources. Engage with live, interactive Wolfram Language examples, reports and files powered by real-time computation. = ksdensity(Data(:,ii),'Support','positive','Function','cdf'. Install Player to: View and interact with Wolfram Notebooks. NumPointCDF = 5 % Number of points to estimate CDF withįor ii = 1:size(Data,2) % for each column of Data If you'd like more control of the plotting features, I'd suggest obtaining the necessary elements to plot from ksdensity using = ksdensity(x) then plotting separately. It looks like you've got the result you want except for the legend and markers. This has been made even easier with cdfplot().

Mathlab pearson cdf files