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LINEAR MODELS AND MATRIX ALGEBRA Part 2

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Multiplication ... Commutative law of multiplication ab = ba. Associative law of addition (a b) ... scalar multiplication: kA=Ak. Commutative, Associative, And ... – PowerPoint PPT presentation

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Title: LINEAR MODELS AND MATRIX ALGEBRA Part 2


1
LINEAR MODELS AND MATRIX ALGEBRA- Part 2
  • Chapter 4
  • Alpha Chiang, Fundamental Methods of Mathematical
    Economics
  • 3rd edition

2
Vector Operations
  • Multiplication of vectors
  • An m x 1 column vector u, and a 1 x n row vector
    v, yield a product uv of dimension m x n. On
    the other hand, a 1 x n row vector u and an n x
    1 column vector v, the product uv will be of
    dimension 1 x 1.
  • Example 1- 2x1, 1x3, 2x3.

3
Vector Operations
  • Example 2. 1x2, 2x1, 1x1
  • As written, uv is a matrix, despite the fact
    that only a single element is present.
  • 1 x 1 matrices behave exactly like scalars with
    respect to addition and multiplication 4 8
    12, 3721
  • a scalar product

4
Vector Operations
  • Example 3. - Given a row vector u 3 6 9,
    find uu. Since u is merely a column vector,
    with elements of u arranged vertically, we have,
  • Note that the product uu gives the sum of
    squares of the elements of u (a scalar).

5
Linear Dependence
  • A set of vectors v1, ,vn is linearly dependent
    if and only if any one of them can be expressed
    as a linear combination of the remaining vectors
    otherwise, they are linearly independent.
  • are linear dependent because v3 is a linear
    combination of v1 and v2

6
Linear Dependence
  • Example 5. v1 5 12 and v2 10 24 are
    linearly dependent because
  • 2v1 25 12 10 24 v2
  • or 2v1-v2 0
  • A set of m-vectors v1, ,vn is linearly dependent
    if and only if there exists a set of scalars k1,
    , kn (not all zero) such that

7
Commutative, Associative, And Distributive Laws
  • In ordinary scalar algebra, additive and
    multiplicative operations obey the commutative,
    associative, and distributive laws
  • Commutative law of addition a b b a
  • Commutative law of multiplication ab ba
  • Associative law of addition (ab) c a
    (bc)
  • Associative law of multiplication ab (c) a(bc)
  • Distributive law a (bc) ab ac

8
Commutative, Associative, And Distributive Laws
  • Matrix Addition commutative and associative
  • Commutative law ABBA

9
Commutative, Associative, And Distributive Laws
  • Associative law (AB) C A (BC)

10
Commutative, Associative, And Distributive Laws
  • Matrix Multiplication not commutative
  • Example

11
Commutative, Associative, And Distributive Laws
  • Example Let u be a 1x3 (a row vector) then
    the corresponding column vector u must be 3x1.
    The product uu will be 1x1 but the product uu
    will be 3x3. Thus obviously, uu ? uu.
  • Exceptions
  • A is a square matrix and B is an identity matrix
  • A is the inverse of B, A B-1
  • scalar multiplication kAAk

12
Commutative, Associative, And Distributive Laws
  • Associative Law (AB)CA(BC)ABC
  • Conformability condition
  • A is mxn, B is nxp, C is pxq
  • Distributive Law
  • A(BC) AB AC pre-multiplication by A
  • (BC)A BA CA post-multiplication by A
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