nmregr2
Calculates least squares estimates using Nelder Mead's simplex method for bivariate data
Contents
Syntax
[q, info] = nmregr2(func, p, x, y, Z, W)
Description
Calculates least squares estimates using Nelder Mead's simplex method for bivariate data
Input
- func: string with name of user-defined function
f = func (p, x, y) with p: np-vector; x: nx-vector; y: ny-vector f: (nx,ny)-matrix with model-predictions for dependent variable
- p: (np,2) matrix with
p(:,1) initial guesses for parameter values p(:,2) binaries with yes or no iteration (optional)
- x: (nx,1)-vector with first independent variable
- y: (ny,1)-vector with second independent variable
- Z: (nx,ny)-matrix with dependent variable
- W: (nx,ny)-matrix with weight coefficients (optional) Default W = ones(nx, ny)/ (nx * ny)
Output
- q: matrix like p, but with least squares estimates
- info: 1 if convergence has been successful; 0 otherwise
Remarks
Calls user-defined function 'func'. Set options with nmregr_options Similar to nrregr2, but slower and a larger bassin of attraction
Example of use
See mydata_regr2