Mercurial > hg > octave-nkf
annotate scripts/signal/arch_fit.m @ 20387:4951982f8a2c stable
intro.txi: Improve documentation in introductory chapter.
* intro.txi: Use 'diary' instead of 'cd' as an example of a command.
Format sample function docstring to match modern usage.
Improve phrasing of a few sentences.
author | Rik <rik@octave.org> |
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date | Mon, 11 May 2015 22:08:26 -0700 |
parents | f1d0f506ee78 |
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1 ## Copyright (C) 1995-2015 Kurt Hornik |
3426 | 2 ## |
3922 | 3 ## This file is part of Octave. |
4 ## | |
5 ## Octave is free software; you can redistribute it and/or modify it | |
6 ## under the terms of the GNU General Public License as published by | |
7016 | 7 ## the Free Software Foundation; either version 3 of the License, or (at |
8 ## your option) any later version. | |
3426 | 9 ## |
3922 | 10 ## Octave is distributed in the hope that it will be useful, but |
3191 | 11 ## WITHOUT ANY WARRANTY; without even the implied warranty of |
12 ## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU | |
3426 | 13 ## General Public License for more details. |
14 ## | |
3191 | 15 ## You should have received a copy of the GNU General Public License |
7016 | 16 ## along with Octave; see the file COPYING. If not, see |
17 ## <http://www.gnu.org/licenses/>. | |
3191 | 18 |
3449 | 19 ## -*- texinfo -*- |
20 ## @deftypefn {Function File} {[@var{a}, @var{b}] =} arch_fit (@var{y}, @var{x}, @var{p}, @var{iter}, @var{gamma}, @var{a0}, @var{b0}) | |
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21 ## Fit an ARCH regression model to the time series @var{y} using the scoring |
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22 ## algorithm in @nospell{Engle's} original ARCH paper. |
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23 ## |
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24 ## The model is |
3191 | 25 ## |
3449 | 26 ## @example |
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27 ## @group |
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28 ## y(t) = b(1) * x(t,1) + @dots{} + b(k) * x(t,k) + e(t), |
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29 ## h(t) = a(1) + a(2) * e(t-1)^2 + @dots{} + a(p+1) * e(t-p)^2 |
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30 ## @end group |
3449 | 31 ## @end example |
3191 | 32 ## |
3449 | 33 ## @noindent |
3499 | 34 ## in which @math{e(t)} is @math{N(0, h(t))}, given a time-series vector |
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35 ## @var{y} up to time @math{t-1} and a matrix of (ordinary) regressors @var{x} |
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36 ## up to @math{t}. The order of the regression of the residual variance is |
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37 ## specified by @var{p}. |
3191 | 38 ## |
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39 ## If invoked as @code{arch_fit (@var{y}, @var{k}, @var{p})} with a positive |
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40 ## integer @var{k}, fit an ARCH(@var{k}, @var{p}) process, i.e., do the above |
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41 ## with the @math{t}-th row of @var{x} given by |
3191 | 42 ## |
3449 | 43 ## @example |
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44 ## [1, y(t-1), @dots{}, y(t-k)] |
3449 | 45 ## @end example |
46 ## | |
47 ## Optionally, one can specify the number of iterations @var{iter}, the | |
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48 ## updating factor @var{gamma}, and initial values @math{a0} and @math{b0} |
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49 ## for the scoring algorithm. |
3449 | 50 ## @end deftypefn |
3191 | 51 |
5428 | 52 ## Author: KH <Kurt.Hornik@wu-wien.ac.at> |
3457 | 53 ## Description: Fit an ARCH regression model |
3191 | 54 |
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55 function [a, b] = arch_fit (y, x, p, iter, gamma, a0, b0) |
3191 | 56 |
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57 if (nargin < 3 || nargin == 6 || nargin > 7) |
6046 | 58 print_usage (); |
3191 | 59 endif |
3426 | 60 |
4030 | 61 if (! (isvector (y))) |
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62 error ("arch_fit: Y must be a vector"); |
3191 | 63 endif |
64 | |
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65 T = length (y); |
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66 y = reshape (y, T, 1); |
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67 [rx, cx] = size (x); |
3191 | 68 if ((rx == 1) && (cx == 1)) |
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69 x = autoreg_matrix (y, x); |
3457 | 70 elseif (! (rx == T)) |
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71 error ("arch_fit: either rows (X) == length (Y), or X is a scalar"); |
3191 | 72 endif |
73 | |
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74 [T, k] = size (x); |
3426 | 75 |
3191 | 76 if (nargin == 7) |
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77 a = a0; |
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78 b = b0; |
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79 e = y - x * b; |
3191 | 80 else |
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81 [b, v_b, e] = ols (y, x); |
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82 a = [v_b, (zeros (1, p))]'; |
3191 | 83 if (nargin < 5) |
84 gamma = 0.1; | |
85 if (nargin < 4) | |
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86 iter = 50; |
3191 | 87 endif |
88 endif | |
89 endif | |
3426 | 90 |
3191 | 91 esq = e.^2; |
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92 Z = autoreg_matrix (esq, p); |
3191 | 93 |
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94 for i = 1 : iter; |
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95 h = Z * a; |
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96 tmp = esq ./ h.^2 - 1 ./ h; |
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97 s = 1 ./ h(1:T-p); |
3191 | 98 for j = 1 : p; |
99 s = s - a(j+1) * tmp(j+1:T-p+j); | |
100 endfor | |
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101 r = 1 ./ h(1:T-p); |
8507 | 102 for j = 1:p; |
3191 | 103 r = r + 2 * h(j+1:T-p+j).^2 .* esq(1:T-p); |
104 endfor | |
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105 r = sqrt (r); |
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106 X_tilde = x(1:T-p, :) .* (r * ones (1,k)); |
3191 | 107 e_tilde = e(1:T-p) .*s ./ r; |
108 delta_b = inv (X_tilde' * X_tilde) * X_tilde' * e_tilde; | |
109 b = b + gamma * delta_b; | |
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110 e = y - x * b; |
3191 | 111 esq = e .^ 2; |
112 Z = autoreg_matrix (esq, p); | |
113 h = Z * a; | |
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114 f = esq ./ h - ones (T,1); |
3191 | 115 Z_tilde = Z ./ (h * ones (1, p+1)); |
116 delta_a = inv (Z_tilde' * Z_tilde) * Z_tilde' * f; | |
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117 a = a + gamma * delta_a; |
3191 | 118 endfor |
3426 | 119 |
3191 | 120 endfunction |
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121 |