1 INTRODUCTION
2 AFFINE MINIMUM‐TRACE UNBIASED ESTIMATION
3 THE GAUSS‐MARKOV THEOREM
4 THE METHOD OF LEAST SQUARES
5 AITKEN'S THEOREM
6 MULTICOLLINEARITY
7 ESTIMABLE FUNCTIONS
8 LINEAR CONSTRAINTS: THE CASEℳ(R) ⊂ ℳ(X)
9 LINEAR CONSTRAINTS: THE GENERAL CASE
10 LINEAR
CONSTRAINTS: THE
CASEℳ(R) ∩ ℳ(X) = {0}
11 A SINGULAR
VARIANCE
MATRIX: THE
CASEℳ(X) ⊂ ℳ(V)
12 A SINGULAR
VARIANCE
MATRIX: THE
CASE
r(X′V
X) = r(X)
13 A SINGULAR VARIANCE MATRIX: THE GENERAL CASE, I
14 EXPLICIT AND IMPLICIT LINEAR CONSTRAINTS
15 THE GENERAL LINEAR MODEL, I
16 A SINGULAR VARIANCE MATRIX: THE GENERAL CASE, II
17 THE GENERAL LINEAR MODEL, II
18 GENERALIZED LEAST SQUARES
19 RESTRICTED LEAST SQUARES