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A course in large sample theory Thomas S. Ferguson
Publisher: Chapman & Hall

The central limit theorem is one of the most remarkable results of the theory of probability [1], which is critical to understand inferential statistics and hypothesis testing [2, 3]. You'll need to learn something about asymptotics at some point, and a good starting place is: 3. Structural Equation Modeling, 14, 505-526. Ferguson, A Course in Large Sample Theory, Chapman & Hall, New York, NY, USA, 1996. Hence, the dependence condition (2.3) allows a stronger dependence within a larger class of random variables and demands more independence within a smaller class. EBay: This is a first year graduate text on large sample theory in statistics. Rics, Harvard University Press, and Ferguson A Course in Large Sample Theory, Chapman and Hall. A Course in Large Sample Theory (CRC/C&h Texts in Statistical Science) by Thomas S. A course in large sample theory. Nearly all topics are covered in their multivariate settings. On the like-lihood ratio test for the number of factors in exploratory factor analysis. "A Course in Large Sample Theory" Chapman & Hall/CRC.