Parsimony in statistical modeling is often discussed in terms of Occam’s razor in the formulation of hypotheses. Address the following:

• Discuss the issues of overfitting versus using parsimony and how this is particularly important in big data analysis.
• Is overfitting more of a problem in the generalized least squares model?
• Discuss some hierarchical methods that do not require the parsimony of generalized least squares model.
• Discuss these hierarchical methods, and provide links to any references that you find on the topic.

Be substantive and clear, and use scholarly examples to reinforce your ideas.