1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
|
function cdf = chi2cdf ( X, n)
df = resize_matrix ( n , size (X) , "" , n);
[cdf,Q] = cdfchi ( "PQ" , X ,df);
endfunction
//main function
function [pval, lm] = arch_test (y, x, p)
// Perform a Lagrange Multiplier (LM) test for conditional heteroscedasticity.
// Description:
// Perform a Lagrange Multiplier (LM) test for conditional heteroscedasticity.
// For a linear regression model
// y = x * b + e
// perform a Lagrange Multiplier (LM) test of the null hypothesis of no conditional heteroscedascity against the alternative of CH(p).
// I.e., the model is
// y(t) = b(1) * x(t,1) + … + b(k) * x(t,k) + e(t),
// given y up to t-1 and x up to t, e(t) is N(0, h(t)) with
// h(t) = v + a(1) * e(t-1)^2 + … + a(p) * e(t-p)^2,
// and the null is a(1) == … == a(p) == 0.
// If the second argument is a scalar integer, k, perform the same test in a linear autoregression model of order k, i.e., with
// [1, y(t-1), …, y(t-k)]
// as the t-th row of x.
// Under the null, LM approximately has a chisquare distribution with p degrees of freedom and pval is the p-value (1 minus the CDF of this distribution at LM) of the test.
// If no output argument is given, the p-value is displayed.
// Calling Sequence
// [pval, lm] = arch_test (y, x, p)
// Parameters
// y: Array-like. Dependent variable of the regression model.
// x: Array-like. Independent variables of the regression model. If x is a scalar integer k, it represents the order of autoregression.
// p : Integer. Number of lagged squared residuals to include in the heteroscedasticity model.
// Returns:
// pval: Float. p-value of the LM test.
// lm: Float. Lagrange Multiplier test statistic.*/
// Dependencies : ols, autoreg_matrix
nargin = argn(2)
if (nargin ~= 3)
error ("arch_test: 3 input arguments required");
end
if (~ (isvector (y)))
error ("arch_test: Y must be a vector");
end
T = max(size(y));
y = matrix (y, T, 1);
[rx, cx] = size (x);
if ((rx == 1) && (cx == 1))
x = autoreg_matrix (y, x);
elseif (~ (rx == T))
error ("arch_test: either rows (X) == length (Y), or X is a scalar");
end
if (~ (isscalar (p) && (modulo (p, 1) == 0) && (p > 0)))
error ("arch_test: P must be a positive integer");
end
[b, v_b, e] = ols (y, x);
Z = autoreg_matrix (e.^2, p);
f = e.^2 / v_b - ones (T, 1);
f = Z' * f;
lm = f' * inv (Z'*Z) * f / 2;
pval = 1 - chi2cdf (lm, p);
endfunction
|