1 files changed, 22 insertions, 22 deletions
diff --git a/macros/arch_fit.sci b/macros/arch_fit.sci
index 2fa462c..b38996a 100644
--- a/macros/arch_fit.sci
+++ b/macros/arch_fit.sci
@@ -1,26 +1,26 @@
-/*
-Dependencies : ols, autoreg_matrix
-Calling Sequence
-      [a, b] = arch_fit (y, x, p)
-      [a, b] = arch_fit (y, x, p, iter, gamma, a0, b0)
-Parameters
-      y(vector) : A time-series data vector up to time t-1 .
-      x (Matrix): A matrix of (ordinary) regressors x up to t.
-      p (scalar): The order of the regression of the residual variance.
-      iter (scaler) : Number of iterations
-      gamma (real number) : updating factor
-      a0 b0 (real numbers) : Initial values for the scoring algorithm
-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 upto 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.
-*/
+
 function [a, b] = arch_fit (y, x, p, iter, gamma, a0, b0)
+// Fit 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)
+//       [a, b] = arch_fit (y, x, p, iter, gamma, a0, b0)
+// Parameters
+//       y(vector) : A time-series data vector up to time t-1 .
+//       x (Matrix): A matrix of (ordinary) regressors x up to t.
+//       p (scalar): The order of the regression of the residual variance.
+//       iter (scaler) : Number of iterations
+//       gamma (real number) : updating factor
+//       a0 b0 (real numbers) : Initial values for the scoring algorithm
+// 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 upto 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.
+
     nargin = argn(2)
     if (nargin < 3 || nargin == 6)
       error("invalid inputs");