Slides14-2010 - Large Sample Theory: Lecture XIV Charles B....

Info iconThis preview shows pages 1–5. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Large Sample Theory: Lecture XIV Charles B. Moss October 3, 2010 Charles B. Moss () Large Sample Theory October 3, 2010 1 / 13 1 Basic Sample Theory 2 Modes of Convergence Charles B. Moss () Large Sample Theory October 3, 2010 2 / 13 Basic Sample Theory The problems set up is that we want to discuss sample theory. I First assume that we want to make an inference, either estimation or some test, based on a sample. I We are interested in how well parameters or statistics based on that sample represent the parameters or statistics of the whole population. The complete statistical term is known as convergence. I Specifically, we are interested in whether or not the statistics calculated on the sample converge toward the population estimates. I Let { X n } be a sequence of samples. We want to demonstrate that statistics based on { X n } converge toward the population statistics for X . Charles B. Moss () Large Sample Theory October 3, 2010 3 / 13 Taking a slightly different tack: The classical assumptions for ordinary least squares (OLS) as presented in White, Halbert Asymptotic Theory for Econometricians. I Theorem 1.1 : The following are the assumptions of the classical linear model F The model is known to be y = X + , < ....
View Full Document

Page1 / 13

Slides14-2010 - Large Sample Theory: Lecture XIV Charles B....

This preview shows document pages 1 - 5. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online