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\hypertarget{methods_8h}{\section{meowpp/math/methods.h File Reference}
\label{methods_8h}\index{meowpp/math/methods.\-h@{meowpp/math/methods.\-h}}
}
{\ttfamily \#include \char`\"{}Matrix.\-h\char`\"{}}\\*
{\ttfamily \#include \char`\"{}Vector.\-h\char`\"{}}\\*
{\ttfamily \#include \char`\"{}utility.\-h\char`\"{}}\\*
{\ttfamily \#include $<$cstdlib$>$}\\*
{\ttfamily \#include $<$vector$>$}\\*
\subsection*{Namespaces}
\begin{DoxyCompactItemize}
\item
namespace \hyperlink{namespacemeow}{meow}
\end{DoxyCompactItemize}
\subsection*{Functions}
\begin{DoxyCompactItemize}
\item
{\footnotesize template$<$class Data , class Weighting\-Class $>$ }\\std\-::vector$<$ Data $>$ \hyperlink{namespacemeow_a43a73b75f2e23c8172d2098d57eaf75a}{meow\-::ransac} (std\-::vector$<$ Data $>$ const \&data, Weighting\-Class const \&w, size\-\_\-t N, \hyperlink{classdouble}{double} p0, \hyperlink{classdouble}{double} P)
\begin{DoxyCompactList}\small\item\em Run the {\bfseries R\-A\-N\-S\-A\-C} method to approach the best solution. \end{DoxyCompactList}\item
{\footnotesize template$<$class Scalar , class F , class J , class I , class Stop $>$ }\\Vector$<$ Scalar $>$ \hyperlink{namespacemeow_a8e4a4baed7fb497f170075648ac95077}{meow\-::levenberg\-Marquardt} (F const \&func, J const \&jaco, I const \&iden, Vector$<$ Scalar $>$ const \&init, Stop const \&stop, \hyperlink{classint}{int} counter=-\/1)
\begin{DoxyCompactList}\small\item\em Run the {\bfseries Levenberg-\/\-Marquardt} method to solve a non-\/linear least squares problem. \end{DoxyCompactList}\end{DoxyCompactItemize}
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