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MCMC-with-Matlab

于 2021-04-30 发布文件大小:1019KB

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马尔可夫链蒙特卡罗（MCMC）入门学习资料，包括MetropolisSampling、Metropolis-Hastings Sampling、Gibbs Sampling。包含文档以及对应的程序！选自2011年MarkSteyvers的Computational Statistics with Matlab(MCMC)(MCMC learning materials of Computational Statistics with Matlab(MCMC) by MarkSteyvers, 2011)

文件列表：

2011_MarkSteyvers_Computational Statistics with Matlab(MCMC).pdf,1194308,2016-09-12
matlablistings
..............\bivexp.m,261,2010-01-21
..............\cauchy.m,120,2010-01-14
..............\ch1_showcumulative1.m,747,2010-01-05
..............\ch1_showdistributions.m,1043,2010-01-05
..............\ch2_bivnormal_MH.m,3004,2011-04-20
..............\ch2_demo2_metropolis.m,1756,2010-01-14
..............\ch2_demo6_MH.m,2106,2010-01-21
..............\ch2_mallows_MH.m,1865,2010-01-21
..............\ch3_posteriorinference_weibull.m,4633,2011-04-21
..............\kendalltau.m,539,2010-01-21
..............\rtdata1.mat,1003,2011-04-21

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DCT_IDCT
to understand the Algorithm go to matlab help in page dct2 and idct2 to get the mathematical expression for M = N = 8, we can calculate the most of hard values and save it as LUTs to speed up the execution now compare our special 8X8 functions with the internal general functions use this code: A = int32(100*rand(8,8)) tic for i = 1 : 1000 IDCT_8X8(DCT_8X8(A)) end toc tic for i = 1 : 1000 idct2(dct2(A)) end toc i had built the general functions too, but with low speed (to understand the Algorithm go to matlab help in page dct2 and idct2 to get the mathematical expressionfor M = N = 8, we can calculate the most of hard values and save it as LUTs to speed up the executionnow compare our special 8X8 functions with the internal general functionsuse this code: A = int32 (100* rand (8,8)) tic for i = 1: 1000 IDCT_8X8 (DCT_8X8 (A)) end toc tic for i = 1: 1000 idct2 (dct2 (A)) end toc i had built the general functions too, but with low speed)

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