15.1 Suppose you have data that consist of n = 10 independent and joint normally distributed random vectors representing multivariate data intensities.

The data might correspond to the output of micro arrays, as used in biology, gray levels, as used in spatial analysis and imaging, or any other collection of intensities. The vectors are p = 100 dimensions in length. How might Bayesian factor analysis be used to obtain a modified data set in whichp < n?