Replaced Line Search with Newton Raphson #1
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The previous version of the ML algorithm was implemented with a line search algorithm which works well for estimating correlations but may become unstable for general Normal mean estimation (especially of the mean to be estimated is outside of the line search range). The current implementation uses a Newton Raphson approach which works well for all sigma/cutoff/x values.
made a small change in order to allow x to be a vector. In which case the mean will be computed and the standard deviation will be divided by sqrt(n).
replaced the standard deviation with the variance in the function input.
Added the extra parameters of the function and added the reference to the arxiv paper.
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The previous version of the ML algorithm was implemented with a line search algorithm which works well for estimating correlations but may become unstable for general Normal mean estimation (especially of the mean to be estimated is outside of the line search range). The current implementation uses a Newton Raphson approach which works well for all sigma/cutoff/x values.