代码搜索：markov
找到约 887 项符合「markov」的源代码
代码结果 887
www.eeworm.com/read/354573/10344951
m process_ex_2.m
% process_ex_2.m determines the parameters lambda and Q for a Markov chain, which can then be used to determine a Markov process
S = [1 2 3 4]; % state space
mu = [0.2 0 0 0.8];
www.eeworm.com/read/146906/5734273
java mc_asset_test.java
/* WARANTY NOTICE AND COPYRIGHT
This program is free software; you can redistribute it and/or
modify it under the terms of the GNU General Public License
as published by the Free Software Foundation;
www.eeworm.com/read/343227/11962653
m ex_cnt.m
%ex_cnt Script to illustrate the three basic models handled by H2m/cnt
% - Poisson mixtures
% - Poisson hidden Markov models
% - Negative-binomial hidden Markov mod
www.eeworm.com/read/253950/12174054
htm demmet1.htm
Netlab Reference Manual demmet1
demmet1
Purpose
Demonstrate Markov Chain Monte Carlo sampling on a Gaussian.
Synopsis
www.eeworm.com/read/150905/12250217
htm demmet1.htm
Netlab Reference Manual demmet1
demmet1
Purpose
Demonstrate Markov Chain Monte Carlo sampling on a Gaussian.
Synopsis
www.eeworm.com/read/449504/7502164
m tvp_markovd.m
% PURPOSE: An example using tvp_markov(),
% prt(),
% plt(),
% time-varying parameter model with Markov switching variances estimation
%---------
www.eeworm.com/read/449504/7502179
m tvp_markovd2.m
% PURPOSE: An example using tvp_markov(), and tvp_garch()
% Compares the estimates from both models
% See Kim and Nelson (1999)
% time-varying parameter model with Markov switchin
www.eeworm.com/read/436995/7757507
m xgmp1.m
% xgmp1.m
% Scope: This MATLAB program generates first order Gauss-Markov sequence,
% plots the generated sequence, histogram, and the normalized auto-
www.eeworm.com/read/492929/6414208
m tvp_markovd.m
% PURPOSE: An example using tvp_markov(),
% prt(),
% plt(),
% time-varying parameter model with Markov switching variances estimation
%---------
www.eeworm.com/read/492929/6414223
m tvp_markovd2.m
% PURPOSE: An example using tvp_markov(), and tvp_garch()
% Compares the estimates from both models
% See Kim and Nelson (1999)
% time-varying parameter model with Markov switchin