小企业网站建设服务,番禺哪里有做网站的公司,大连甘井子区二手房,织梦首饰网站模板时序分解 | Matlab实现贝叶斯变化点检测与时间序列分解 目录 时序分解 | Matlab实现贝叶斯变化点检测与时间序列分解效果一览基本介绍程序设计参考资料 效果一览 基本介绍 Matlab实现贝叶斯变化点检测与时间序列分解 1.Matlab实现贝叶斯变化点检测与时间序列分解#xff0c;完…时序分解 | Matlab实现贝叶斯变化点检测与时间序列分解 目录 时序分解 | Matlab实现贝叶斯变化点检测与时间序列分解效果一览基本介绍程序设计参考资料 效果一览 基本介绍 Matlab实现贝叶斯变化点检测与时间序列分解 1.Matlab实现贝叶斯变化点检测与时间序列分解完整源码和数据 BEAST突变、季节性和趋势的贝叶斯估计是一种快速、通用的贝叶斯模型平均算法用于将时间序列或1D序列数据分解为单个分量如突变、趋势和周期性/季节性变化如赵等人2019所述。BEAST可用于变化点检测例如断点、结构中断、状态变化或异常、趋势分析、时间序列分解例如趋势与季节性、时间序列分割和中断时间序列分析。 2.运行主程序main即可其余为函数无需运行运行环境matlab2020及以上。 贝叶斯变化点检测和时间序列分解是两种在时间序列分析中常用的技术。 贝叶斯变化点检测Bayesian Change Point Detection是一种用于检测时间序列中突变点或结构变化的方法。它基于贝叶斯统计方法通过考虑数据的先验分布和后验分布来确定变化点的位置和数量。该方法可以应用于多种类型的时间序列。 时间序列分解Time Series Decomposition是将时间序列分解为不同组成部分的过程。通常一个时间序列可以分解为趋势Trend、季节性Seasonality和残差Residual三个部分。趋势表示时间序列的长期趋势变化季节性表示时间序列在固定周期内的重复模式而残差则表示无法由趋势和季节性解释的随机波动。时间序列分解可以帮助我们更好地理解时间序列的结构和特征以及对序列进行预测和分析。
程序设计
完整源码和数据获取方式Matlab实现贝叶斯变化点检测与时间序列分解。
%% get values from keys. The last arg is the default value if the key is missing from varagin/KeyListstart GetValueByKey(KeyList, ValList, start, []);deltat GetValueByKey(KeyList, ValList, deltat, []);time GetValueByKey(KeyList, ValList, time, []); period GetValueByKey(KeyList, ValList, period, []); nsamples_per_period GetValueByKey(KeyList, ValList, freq, []); season GetValueByKey(KeyList, ValList, season, harmonic); sorder_minmax GetValueByKey(KeyList, ValList, sorder.minmax, [1,5]); scp_minmax GetValueByKey(KeyList, ValList, scp.minmax, [0,10]); sseg_min GetValueByKey(KeyList, ValList, sseg.min, []); sseg_leftmargin GetValueByKey(KeyList, ValList, sseg.leftmargin, []); sseg_rightmargin GetValueByKey(KeyList, ValList, sseg.rightmargin, []); deseasonalize GetValueByKey(KeyList, ValList, deseasonalize, false); detrend GetValueByKey(KeyList, ValList, detrend, false); torder_minmax GetValueByKey(KeyList, ValList, torder.minmax, [0,1]); tcp_minmax GetValueByKey(KeyList, ValList, tcp.minmax, [0,10]); tseg_min GetValueByKey(KeyList, ValList, tseg.min, []);tseg_leftmargin GetValueByKey(KeyList, ValList, tseg.leftmargin, []); tseg_rightmargin GetValueByKey(KeyList, ValList, tseg.rightmargin, []); precValue GetValueByKey(KeyList, ValList, precValue, 1.5); precPriorType GetValueByKey(KeyList, ValList, precPriorType, componentwise); hasOutlierCmpnt GetValueByKey(KeyList, ValList, hasOutlier, []); ocp_max GetValueByKey(KeyList, ValList, ocp.max, 10); mcmc_seed GetValueByKey(KeyList, ValList, mcmc.seed, 0); mcmc_samples GetValueByKey(KeyList, ValList, mcmc.samples, 8000);mcmc_thin GetValueByKey(KeyList, ValList, mcmc.thin, 5); mcmc_burnin GetValueByKey(KeyList, ValList, mcmc.burnin, 200);mcmc_chainNumber GetValueByKey(KeyList, ValList, mcmc.chains, 3); ci GetValueByKey(KeyList, ValList, ci, false); printProgressBar GetValueByKey(KeyList, ValList, print.progress, true); printOptions GetValueByKey(KeyList, ValList, print.options, true); quiet GetValueByKey(KeyList, ValList, quiet, false); gui GetValueByKey(KeyList, ValList, gui, false); methods GetValueByKey(KeyList, ValList, method, bayes); %% Convert the opt parameters to the individual option parameters (e.g., metadata, prior, mcmc, and extra)%......Start of displaying MetaData ......metadata [];metadata.isRegularOrdered true;metadata.season season;metadata.time time;metadata.startTime start;metadata.deltaTime deltat;if isempty(period) ~isempty(deltat) ~isempty(nsamples_per_period) ~strcmp(season, none)periodnsamples_per_period*deltat;end metadata.period period;if strcmp(metadata.season, svd)% if isempty(freq)|| freq 1.1 || isnan(freq)% error(When seasonsvd, freq must be specified and larger than 1.);% end% metadata.svdTerms svdbasis(y, freq, deseasonalize);endmetadata.missingValue NaN;metadata.maxMissingRate 0.75;metadata.deseasonalize deseasonalize;metadata.detrend detrend;metadata.hasOutlierCmpnt hasOutlierCmpnt;
%........End of displaying MetaData ........%......Start of displaying prior ......prior [];prior.modelPriorType 1;if ~strcmp(metadata.season, none) prior.seasonMinOrder sorder_minmax(1);prior.seasonMaxOrder sorder_minmax(2);prior.seasonMinKnotNum scp_minmax(1);prior.seasonMaxKnotNum scp_minmax(2); prior.seasonMinSepDist sseg_min;prior.seasonLeftMargin sseg_leftmargin;prior.seasonRightMargin sseg_rightmargin;end prior.trendMinOrder torder_minmax(1);prior.trendMaxOrder torder_minmax(2);prior.trendMinKnotNum tcp_minmax(1);prior.trendMaxKnotNum tcp_minmax(2);prior.trendMinSepDist tseg_min;prior.trendLeftMargin tseg_leftmargin;prior.trendRightMargin tseg_rightmargin;if hasOutlierCmpntprior.outlierMaxKnotNum ocp_max;endprior.precValue precValue;prior.precPriorType precPriorType;
%......End of displaying pripr ......%......Start of displaying mcmc ......mcmc [];mcmc.seed mcmc_seed;mcmc.samples mcmc_samples;mcmc.thinningFactor mcmc_thin;mcmc.burnin mcmc_burnin;mcmc.chainNumber mcmc_chainNumber;%mcmc.maxMoveStepSize 28mcmc.trendResamplingOrderProb 0.1000;mcmc.seasonResamplingOrderProb 0.1700;mcmc.credIntervalAlphaLevel 0.950;
%......End of displaying mcmc ......%......Start of displaying extra ......extra [];extra.dumpInputData true;extra.whichOutputDimIsTime 1;extra.computeCredible ci;extra.fastCIComputation true;extra.computeSeasonOrder true;extra.computeTrendOrder true;extra.computeSeasonChngpt true;extra.computeTrendChngpt true;extra.computeSeasonAmp ~strcmp(metadata.season, svd);extra.computeTrendSlope true;extra.tallyPosNegSeasonJump false;extra.tallyPosNegTrendJump false;extra.tallyIncDecTrendJump false;extra.printProgressBar printProgressBar;extra.printOptions printOptions;extra.quiet quiet;extra.consoleWidth 70;extra.numThreadsPerCPU 2;extra.numParThreads 0;
%......End of displaying extra ......if (gui)outRbeast( beastv4demo, y, metadata, prior, mcmc, extra);elseoutRbeast( strcat(beast_,methods), y, metadata, prior, mcmc, extra);endend参考资料 [1] https://blog.csdn.net/kjm13182345320/article/details/129215161 [2] https://blog.csdn.net/kjm13182345320/article/details/128105718
