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Diffstat (limited to 'macros/arch_fit.sci')
| -rw-r--r-- | macros/arch_fit.sci | 35 |
1 files changed, 35 insertions, 0 deletions
diff --git a/macros/arch_fit.sci b/macros/arch_fit.sci new file mode 100644 index 0000000..3e431a6 --- /dev/null +++ b/macros/arch_fit.sci @@ -0,0 +1,35 @@ +function [A, B] = arch_fit(Y, varargin) +//This functions fits an ARCH regression model to the time series Y using the scoring algorithm in Engle's original ARCH paper. +//Calling Sequence +//[A, B] = arch_fit (Y, X, P, ITER, GAMMA, A0, B0) +//Parameters +//Description +//Fit an ARCH regression model to the time series Y using the scoring algorithm in Engle's original ARCH paper. +// +//The model is +// +// y(t) = b(1) * x(t,1) + ... + b(k) * x(t,k) + e(t), +// h(t) = a(1) + a(2) * e(t-1)^2 + ... + a(p+1) * e(t-p)^2 +// +//in which e(t) is N(0, h(t)), given a time-series vector Y up to time t-1 and a matrix of (ordinary) regressors X up to t. The order of the regression of the residual variance is specified by P. +// +//If invoked as 'arch_fit (Y, K, P)' with a positive integer K, fit an ARCH(K, P) process, i.e., do the above with the t-th row of X given by +// +// [1, y(t-1), ..., y(t-k)] +// +//Optionally, one can specify the number of iterations ITER, the updating factor GAMMA, and initial values a0 and b0 for the scoring algorithm. +funcprot(0); +rhs = argn(2); +lhs=argn(1); +if(rhs<7 | rhs>7) +error("Wrong number of input arguments."); +end +if (lhs<2 | lhs>2) + error("Wrong number of output arguments."); +end + + select(rhs) + case 7 then + [A, B] = callOctave("arch_fit",Y, varargin(1), varargin(2), varargin(3), varargin(4), varargin(5), varargin(6)); + end +endfunction |