# Sampling Arbitrary data

**sweissblaug**, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)

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MCMC Sampling:

MCMC sampling is a method that can simulate from any multivariate densities as long as one has the full conditionals. Full conditionals in this case are models of a particular variable given all other variables. For more concreteness; suppose we have a dataset with n variables (x1, x2, … xn). The estimated full conditionals in this case are:

**Simulated Iris Data Set**

The simulated dataset shows sharper boundaries between points that are not found in original dataset. For example, the scatterplot between Sepal.Length and Sepal.Width shows a sharp boundary at approximately 5 Sepal.Length in simulated data but it more gradual in original data.

Conclusion:

This post discussed a method to simulate an arbitrary dataset. While I cannot build a model to distinguish the two datasets, visually they are distinguishable.

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**sweissblaug**.

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