matmin

 [par,err,gof,stat] = matmin(gof_func,inpar,freepar,func,y,...)

 Use Minuit to fit an arbitrary function and return
 fitted parameters WITH THEIR ERRORS!

 gof_func is the goodness-of-fit rule to use - chisq, logl etc.
 inpar are the initial parameter values to start minimization from.
 freepar is a logical array indicating if the corresponding parameter
 par should be varied in the fit. If freepar=[] then all par are
 taken to be free.
 func is the name of an N parameter user supplied MATLAB
 function to fit which must have the form [y]=func(par,x).
 y,... are the data required to calc gof. For logl
 minimum would be n,x - for opt chisq min would be y,e,x -
 but y,e,x1,x2 with [y]=func(par,x1,x2) etc is needed
 for some problems.

 par are the output parameter values and err the errors
 on those parameters.
 gof is the goodness-of-fit at the par values given (chi
 square or -2 times the log joint probability).
 stat is the status of the fit (see MINUIT manual - 3 is AOK).

 eg: [x,n]=hfill(randn(1,1000),100,-3,3);
     [p,pe]=matmin('chisq',[30,0,1],[],'gauss',n,sqrt(n),x)
     [p,pe]=matmin('logl',[30,0,1],[],'gauss',n,x)

0001 function [par,err,gof,stat] = matmin(gof_func,inpar,freepar,func,y,varargin)
0002 % [par,err,gof,stat] = matmin(gof_func,inpar,freepar,func,y,...)
0003 %
0004 % Use Minuit to fit an arbitrary function and return
0005 % fitted parameters WITH THEIR ERRORS!
0006 %
0007 % gof_func is the goodness-of-fit rule to use - chisq, logl etc.
0008 % inpar are the initial parameter values to start minimization from.
0009 % freepar is a logical array indicating if the corresponding parameter
0010 % par should be varied in the fit. If freepar=[] then all par are
0011 % taken to be free.
0012 % func is the name of an N parameter user supplied MATLAB
0013 % function to fit which must have the form [y]=func(par,x).
0014 % y,... are the data required to calc gof. For logl
0015 % minimum would be n,x - for opt chisq min would be y,e,x -
0016 % but y,e,x1,x2 with [y]=func(par,x1,x2) etc is needed
0017 % for some problems.
0018 %
0019 % par are the output parameter values and err the errors
0020 % on those parameters.
0021 % gof is the goodness-of-fit at the par values given (chi
0022 % square or -2 times the log joint probability).
0023 % stat is the status of the fit (see MINUIT manual - 3 is AOK).
0024 %
0025 % eg: [x,n]=hfill(randn(1,1000),100,-3,3);
0026 %     [p,pe]=matmin('chisq',[30,0,1],[],'gauss',n,sqrt(n),x)
0027 %     [p,pe]=matmin('logl',[30,0,1],[],'gauss',n,x)
0028 
0029 if(isempty(freepar))
0030   freepar=ones(size(inpar));
0031 end
0032 
0033 if(size(inpar)~=size(freepar))
0034   error('freepar must be same size as inpar (or empty)')
0035 end
0036 
0037 [par,err,gof,stat] = matminc(gof_func,inpar,freepar,func,y,varargin{:});
0038 
0039 return