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/439462/7708281
m music.m
function w=music(y,n,m)
%
% The Root MUSIC method for frequency estimation.
%
% w=music(y,n,m);
%
% y -> the data vector
% n -> the model order
% m -> the order of the co
www.eeworm.com/read/299459/7850637
m demo_mmgauss.m
function demo_mmgauss(action,hfigure,varargin)
% DEMO_MMGAUSS Demo on minimax estimation for Gaussian.
%
% Synopsis:
% demo_mmgauss
%
% Description:
% demo_mmgauss demonstrates the minimax estimati
www.eeworm.com/read/199440/7853112
m transmat_train_observed.m
function [transmat, initState] = transmat_train_observed(labels, nstates, varargin)
% transmat_train_observed ML estimation from fully observed data
% function [transmat, initState] = transmat_trai
www.eeworm.com/read/198546/7928923
m egarch.m
function [parameters, likelihood, stderrors, robustSE, ht, scores]=egarch(data,p,o,q,errors, options, startingvals);
% PURPOSE:
% E_GARCH(P,Q) parameter estimation with different error distribut
www.eeworm.com/read/198546/7928960
m skewt_garch.m
function [parameters, likelihood, stderrors, robustSE, ht, scores] = skewt_garch(data , p , q , startingvals, options)
% PURPOSE:
% SKEWT_GARCH(P,Q) parameter estimation with different error dis
www.eeworm.com/read/196844/8054893
m transmat_train_observed.m
function [transmat, initState] = transmat_train_observed(labels, nstates, varargin)
% transmat_train_observed ML estimation from fully observed data
% function [transmat, initState] = transmat_trai
www.eeworm.com/read/196832/8055358
m contents.m
% CHMMBOX, version 1.2, Iead Rezek, Oxford University, February 2001
% Matlab toolbox for Max. aposteriori estimation of two chain Coupled
% Hidden Markov Models
%
% (Adapted from Hidden Markov Toolbo
www.eeworm.com/read/243093/12964956
m megdemo.m
%% load MEG data (see NeuroImage 2004 paper)
load megdata
%% Estimation
% Reduce dimension from 122 ordinal signals to 20
% Resample 25 times using random initial conditions and bootstrapping
% (u
www.eeworm.com/read/140880/13054425
todo
$Id: TODO,v 1.4 1998/02/23 09:57:48 kanungo Exp kanungo $
-- Documentation: Tutorial with theory, description of software,
and applications.
+added some
-- Estimation from multiple observatio
www.eeworm.com/read/140851/13059468
m transmat_train_observed.m
function [transmat, initState] = transmat_train_observed(labels, nstates, varargin)
% transmat_train_observed ML estimation from fully observed data
% function [transmat, initState] = transmat_trai