diff options
Diffstat (limited to 'Eigen/src/Regression/Regression.h')
| -rw-r--r-- | Eigen/src/Regression/Regression.h | 24 |
1 files changed, 12 insertions, 12 deletions
diff --git a/Eigen/src/Regression/Regression.h b/Eigen/src/Regression/Regression.h index 88e4e8921..b03799f49 100644 --- a/Eigen/src/Regression/Regression.h +++ b/Eigen/src/Regression/Regression.h @@ -76,17 +76,17 @@ * Let's now describe precisely the parameters: * @param numPoints the number of points * @param points the array of pointers to the points on which to perform the linear regression - * @param retCoefficients pointer to the vector in which to store the result. - This vector must be of the same type and size as the - data points. The meaning of its coords is as follows. - For brevity, let \f$n=Size\f$, - \f$r_i=retCoefficients[i]\f$, - and \f$f=funcOfOthers\f$. Denote by - \f$x_0,\ldots,x_{n-1}\f$ - the n coordinates in the n-dimensional space. - Then the result equation is: - \f[ x_f = r_0 x_0 + \cdots + r_{f-1}x_{f-1} - + r_{f+1}x_{f+1} + \cdots + r_{n-1}x_{n-1} + r_n. \f] + * @param result pointer to the vector in which to store the result. + This vector must be of the same type and size as the + data points. The meaning of its coords is as follows. + For brevity, let \f$n=Size\f$, + \f$r_i=retCoefficients[i]\f$, + and \f$f=funcOfOthers\f$. Denote by + \f$x_0,\ldots,x_{n-1}\f$ + the n coordinates in the n-dimensional space. + Then the result equation is: + \f[ x_f = r_0 x_0 + \cdots + r_{f-1}x_{f-1} + + r_{f+1}x_{f+1} + \cdots + r_{n-1}x_{n-1} + r_n. \f] * @param funcOfOthers Determines which coord to express as a function of the others. Coords are numbered starting from 0, so that a value of 0 means \f$x\f$, 1 means \f$y\f$, @@ -183,7 +183,7 @@ void fitHyperplane(int numPoints, VectorType diff = (*(points[i]) - mean).conjugate(); covMat += diff * diff.adjoint(); } - + // now we just have to pick the eigen vector with smallest eigen value SelfAdjointEigenSolver<CovMatrixType> eig(covMat); result->start(size) = eig.eigenvectors().col(0); |