gasurv
Calculates max likelihood estimates using a genetic algorithm for univariate data
Contents
Syntax
[q, info, endPop, bPop, traceInfo] = gasurv(func, p, varargin)
Description
Calculates max likelihood estimates using a genetic algorithm for univariate data
Input
- func: string with name of user-defined function
f = func (p, tn) with
p: k-vector with parameters; tn: (n,c)-matrix; f: n-vector
[f1, f2, ...] = func (p, tn1, tn2, ...) with p: k-vector and
tni: (ni,k)-matrix; fi: ni-vector with model predictions
The dependent variable in the output f; For tn see below.- p: (k,2) matrix with
p(:,1) initial guesses for parameter values p(:,2) binaries with yes or no iteration (optional)
- tni (read as tn1, tn2, .. ): (ni,2) matrix with
tni(:,1) time: must be increasing with rows tni(:,2) number of survivors: must be non-increasing with rows tni(:,3, 4, ... ) data-pont specific information data (optional) The number of data matrices tn1, tn2, ... is optional but >0
Output
- q: matrix like p, but with ml-estimates
- info: 1 if convergence has been successful; 0 otherwise
- endPop: the final population: individual in each row; last column is minus weighted sum of squares
- bPop: a trace of the best population
- traceInfo: a matrix of best and means of the ga for each generation
Remarks
Set options with garegr_options Similar to nrsurv, but slower and a larger bassin of attraction.
Modified from gaot package version 1996/02/02: C.R. Houck, J.Joines, and M.Kay. A genetic algorithm for function optimization: A Matlab implementation. ACM Transactions on Mathmatical Software, Submitted 1996 binary and order options removed
gasurv calls for: User-defined function: 'func'
Crossover Operators: simplexover heuristicxover arithxover Mutation Operators: boundarymutation multinonunifmutation nonunifmutation unifmutation Selection Functions: normgeomselect roulette tournselect Utility functions: cat Option setting: garegr_options
Example of use
<../mydata_surv.m *mydata_surv*>