nmvcregr
Calculates ml estimates using Nelder Mead's simplex method with constant variation coefficient
Contents
Syntax
[q, info] = nmvcregr(func, p, varargin)
Description
Calculates ml estimates using Nelder Mead's simplex method with constant variation coefficient
Input
- func: string with name of user-defined function
f = func (p, xyw) with
p: k-vector with parameters; xyw: (n,c)-matrix; f: n-vector
[f1, f2, ...] = func (p, xyw1, xyw2, ...) with p: k-vector and
xywi: (ni,k)-matrix; fi: ni-vector with model predictions
The dependent variable in the output f; For xyw see below.- p: (k,2) matrix with
p(:,1) initial guesses for parameter values p(:,2) binaries with yes or no iteration (optional)
- xyzi (read as xyw1, xyw2, .. ): (ni,3) matrix with
xywi(:,1) independent variable i xywi(:,2) dependent variable i xywi(:,3) weight coefficients i (optional) xywi(:,>3) data-pont specific information data (optional) The number of data matrices xyw1, xyw2, ... is optional but >0
Output
q: matrix like p, but with ml estimates info: 1 if convergence has been successful; 0 otherwise
Remarks
Calls user-defined function 'func'. Set options with nmregr_options. Similar to nmregr, but standard deviation proportional to mean