deletions | additions       diff --git a/method.tex b/method.tex  index ae376f6..e9cfe19 100644  --- a/method.tex  +++ b/method.tex 
...
\setcounter{section}{4}  \section{Method}  \subsection{The Square Root Information Filter}  The Square Root Information Filter (SRIF) was originally developed by Bierman in 1977 [ref]. The algorithm minimizes $\chi^2$ for time series data with Gaussian errors, and was based on the Kalman filter algorithm. SRIF is more stable, more accurate, and faster than the current algorithm used in \textbf{shape}. SRIF is also more numerically stable (and, in some cases faster) than a standard Jacobi-based steepest descent $\chi^2$-minimzation routine (SDR). My implmentation of SRIF includes some changes to the original algorithm, which will be discussed in section blah.blah. \par  The fundamental difference between SRIF algorithm and a classic SDR is the use of matrix square roots and Householder operations for increased numerical stability.  \subsection{poop}  poop  The \emph{characteristic polynomial} $\chi(\lambda)$ of the  $3 \times 3$~matrix