STAT 445 Study Guide - Final Guide: Orthogonal Matrix, Diagonal Matrix, Maximum Likelihood Estimation

• School: Simon Fraser University
• Department: Statistics
• Course: STAT 445
• Professor: Michelle Zhou

Document Summary

, xp) [ , ] (not necessarily mvn) Find f = (f1, , fm) such that. X = + lf + or where. Xi = i + i1f1 + + imfm + i i = 1, , p: m p, i: ith speci c factor, i = 1, . , p: fj: jth common factor, j = 1, . , m: ij: loading of the ith variable on the jth factor; l: matrix of factor loading. Model assumptions: f = (f1, f2, . , fm) with e(f ) = 0 and cov(f ) = i: = ( 1, 2, . , p) with e( ) = 0 and cov( ) = = diag{ 1, , p}: f and are independent. V ar(xi) = ii = h2 i + i. H2 i = 2 i1 + + 2 im is called communality.