formated source documentation pattern for generating docs

1 files changed, 18 insertions, 18 deletions

diff --git a/macros/ols.sci b/macros/ols.sci
index f2b0b35..e9a9148 100644
--- a/macros/ols.sci
+++ b/macros/ols.sci
@@ -1,22 +1,22 @@
-/*
-Description:
-            Ordinary least squares estimation.
-            OLS applies to the multivariate model y = x*b + e with mean (e) = 0 and
-            cov (vec (e)) = kron (s, I). where y is a t by p matrix, x is a t by k matrix, b is a k by p matrix, and e is a t by p matrix.
-            Each row of y and x is an observation and each column a variable.
-            The return values beta, sigma, and r are defined as follows.
-Calling Sequence:
-            [beta, sigma, r] = ols (y, x)
-Arguments:
-            beta:
-                The OLS estimator for b. beta is calculated directly via inv (x'*x) * x' * y if the matrix x'*x is of full rank. Otherwise, beta = pinv (x) * y where pinv (x) denotes the pseudoinverse of x.
-            sigma
-                The OLS estimator for the matrix s,
-                sigma = (y-x*beta)'* (y-x*beta) / (t-rank(x))
-            r
-                The matrix of OLS residuals, r = y - x*beta.
-*/
+
 function [bt, sigma, r] = ols (y, x)
+// Description:
+//             Ordinary least squares estimation.
+//             OLS applies to the multivariate model y = x*b + e with mean (e) = 0 and
+//             cov (vec (e)) = kron (s, I). where y is a t by p matrix, x is a t by k matrix, b is a k by p matrix, and e is a t by p matrix.
+//             Each row of y and x is an observation and each column a variable.
+//             The return values beta, sigma, and r are defined as follows.
+// Calling Sequence:
+//             [beta, sigma, r] = ols (y, x)
+// Arguments:
+//             beta:
+//                 The OLS estimator for b. beta is calculated directly via inv (x'*x) * x' * y if the matrix x'*x is of full rank. Otherwise, beta = pinv (x) * y where pinv (x) denotes the pseudoinverse of x.
+//             sigma
+//                 The OLS estimator for the matrix s,
+//                 sigma = (y-x*beta)'* (y-x*beta) / (t-rank(x))
+//             r
+//                 The matrix of OLS residuals, r = y - x*beta.
+
     function [u , p] = formatted_chol(z)
       //p flags whether the matrix A was positive definite and chol does not fail. A zero value of p indicates that matrix A is positive definite and R gives the factorization. Otherwise, p will have a positive value.
       ierr  = execstr (" u = chol (z);",'errcatch' )