代码搜索：ESTIMATION
找到约 3,786 项符合「ESTIMATION」的源代码
代码结果 3,786
www.eeworm.com/read/356808/10221069
m d_rivtr.m
%D_RIVTR HOSA Demo: Adaptive AR parameter estimation - transversal form
%
echo off
% A. Swami Oct 18, 1997.
% Copyright (c) 1991-2001 by United Signals & Systems, Inc.
% $Revision:
www.eeworm.com/read/280595/10312429
m~ mlsigmoid.m~
function varargout=mlsigmoid(arg1,arg2,arg3)
% MLSIGMOID Fitting a sigmoid function using ML estimation.
%
% Synopsis:
% model = mlsigmoid(data,options)
%
% Description:
% model = mlsigmoid(data,opt
www.eeworm.com/read/280595/10312453
m mlsigmoid.m
function varargout=mlsigmoid(arg1,arg2,arg3)
% MLSIGMOID Fitting a sigmoid function using ML estimation.
%
% Synopsis:
% model = mlsigmoid(data,options)
%
% Description:
% model = mlsigmoid(data,opt
www.eeworm.com/read/466230/7041261
m confuneq_ms_ar.m
% Equality and inequality constraints for ms(k)-ar(p) estimation
function [c,ceq]=confuneq_MS_AR(param)
global k_global; % Getting k
k=k_global;
% Organizinh transition probabilities
fo
www.eeworm.com/read/450295/7486053
m confuneq_ms_ar.m
% Equality and inequality constraints for ms(k)-ar(p) estimation
function [c,ceq]=confuneq_MS_AR(param)
global k_global; % Getting k
k=k_global;
% Organizinh transition probabilities
fo
www.eeworm.com/read/449504/7502921
m contents.m
% first-order spatial autoregressive model estimation functions
%
% compare_weights : An example of model comparison using far_g
% f2_far : evaluate the log-likelihood for ML rho,sigma valu
www.eeworm.com/read/299459/7850905
m~ mlsigmoid.m~
function varargout=mlsigmoid(arg1,arg2,arg3)
% MLSIGMOID Fitting a sigmoid function using ML estimation.
%
% Synopsis:
% model = mlsigmoid(data,options)
%
% Description:
% model = mlsigmoid(data,opt
www.eeworm.com/read/299459/7850919
m mlsigmoid.m
function varargout=mlsigmoid(arg1,arg2,arg3)
% MLSIGMOID Fitting a sigmoid function using ML estimation.
%
% Synopsis:
% model = mlsigmoid(data,options)
%
% Description:
% model = mlsigmoid(data,opt
www.eeworm.com/read/312163/13617597
m~ mlsigmoid.m~
function varargout=mlsigmoid(arg1,arg2,arg3)
% MLSIGMOID Fitting a sigmoid function using ML estimation.
%
% Synopsis:
% model = mlsigmoid(data,options)
%
% Description:
% model = mlsigmoid(data,opt
www.eeworm.com/read/312163/13617604
m mlsigmoid.m
function varargout=mlsigmoid(arg1,arg2,arg3)
% MLSIGMOID Fitting a sigmoid function using ML estimation.
%
% Synopsis:
% model = mlsigmoid(data,options)
%
% Description:
% model = mlsigmoid(data,opt