首页 Matlab Copula工具箱_Matlab Copula Toolbox.zip

Matlab Copula工具箱_Matlab Copula Toolbox.zip

上传者： Mmnnnbb123 | 上传时间： 2025-12-17 10:44:55 | 文件大小： 198KB | 文件类型： ZIP
Matlab Copula工具箱是一种专门用于Matlab环境下的数学计算和数据分析的工具包，它提供了对Copula理论与方法的实现。Copula理论是一种用于分析随机变量之间依赖关系的数学工具，近年来在金融、保险、工程等多个领域得到了广泛应用。 Copula工具箱内置了大量的Copula模型，包括常用的阿基米德Copula、椭圆Copula以及一些特殊构造的Copula函数。这些模型可以帮助用户研究多个随机变量之间的联合分布特性，尤其是它们的边缘分布和联合分布之间的相关结构。 该工具箱支持模型的拟合、估计和选择。用户可以通过对历史数据的分析，选取合适的Copula模型来描述变量间的依赖关系，并进一步进行风险管理和决策分析。工具箱中还包含了对Copula模型参数估计的各种方法，如极大似然估计和矩估计等。 此外，Matlab Copula工具箱还提供了丰富的模拟功能。用户可以通过它生成具有特定依赖结构的模拟数据，这在金融产品的定价、保险风险评估以及多变量分析中都是非常有用的功能。 在操作方面，该工具箱具有良好的用户界面和编程接口，使得使用者可以方便地进行各类Copula模型的应用。同时，由于其底层基于Matlab强大的数值计算能力，因此在进行复杂计算时，也有着不错的性能表现。 工具箱中还包含大量的应用案例和演示脚本，为初学者和专业用户提供学习和参考。通过这些案例，用户可以更直观地理解Copula模型的应用场景和方法步骤。 Matlab Copula工具箱在金融工程领域的应用尤为突出，例如在资产组合优化、信用风险评估以及衍生品定价中，Copula模型能够帮助用户构建更加精确的风险模型，从而提高投资决策的科学性和准确性。在保险行业，Copula工具箱也常被用于分析和管理保险组合的风险。 整体来看，Matlab Copula工具箱是一个功能强大且应用广泛的统计分析工具，它能够帮助研究人员和工程师们在多个领域内进行复杂的数据分析和模型构建。随着数据分析需求的不断增长，这类专业工具箱的应用前景将更加广阔。

文件下载

资源详情

[{"title":"（ 164 个子文件 198KB ） Matlab Copula工具箱_Matlab Copula Toolbox.zip","children":[{"title":"empcopulapdf_c.c <span style='color:#111;'> 4.87KB </span>","children":null,"spread":false},{"title":"mvArchimedeanCopula_input.csv <span style='color:#111;'> 54B </span>","children":null,"spread":false},{"title":"claytonPdf3D_output.csv <span style='color:#111;'> 48B </span>","children":null,"spread":false},{"title":"eqdisttest2_input1.csv <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"eqdisttest1_input1.csv <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"eqdisttest2_input2.csv <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"eqdisttest1_input2.csv <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"rlogseries_output1.csv <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"rlogseries_output3.csv <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"gumbelPdf3D_output.csv <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"rlogseries_output2.csv <span style='color:#111;'> 47B </span>","children":null,"spread":false},{"title":"rF01Frank_output2.csv <span style='color:#111;'> 46B </span>","children":null,"spread":false},{"title":"frankPdf3D_output.csv <span style='color:#111;'> 46B </span>","children":null,"spread":false},{"title":"retstable_output3.csv <span style='color:#111;'> 46B </span>","children":null,"spread":false},{"title":"rF01Frank_output1.csv <span style='color:#111;'> 46B </span>","children":null,"spread":false},{"title":"retstable_output1.csv <span style='color:#111;'> 46B </span>","children":null,"spread":false},{"title":"retstable_output2.csv <span style='color:#111;'> 46B </span>","children":null,"spread":false},{"title":"rF01Frank_input2.csv <span style='color:#111;'> 45B </span>","children":null,"spread":false},{"title":"rstable1_output1.csv <span style='color:#111;'> 45B </span>","children":null,"spread":false},{"title":"rstable1_output2.csv <span style='color:#111;'> 45B </span>","children":null,"spread":false},{"title":"retstable_input2.csv <span style='color:#111;'> 45B </span>","children":null,"spread":false},{"title":"retstable_input3.csv <span style='color:#111;'> 45B </span>","children":null,"spread":false},{"title":"rF01Frank_input1.csv <span style='color:#111;'> 45B </span>","children":null,"spread":false},{"title":"retstable_input1.csv <span style='color:#111;'> 45B </span>","children":null,"spread":false},{"title":"rSibuya_output1.csv <span style='color:#111;'> 44B </span>","children":null,"spread":false},{"title":"rSibuya_output2.csv <span style='color:#111;'> 44B </span>","children":null,"spread":false},{"title":"rF01Joe_output2.csv <span style='color:#111;'> 44B </span>","children":null,"spread":false},{"title":"rF01Joe_output1.csv <span style='color:#111;'> 44B </span>","children":null,"spread":false},{"title":"rF01Joe_input1.csv <span style='color:#111;'> 43B </span>","children":null,"spread":false},{"title":"rF01Joe_input2.csv <span style='color:#111;'> 43B </span>","children":null,"spread":false},{"title":"clayton_v01_2.csv <span style='color:#111;'> 42B </span>","children":null,"spread":false},{"title":"clayton_v01_1.csv <span style='color:#111;'> 42B </span>","children":null,"spread":false},{"title":"rlog_output2.csv <span style='color:#111;'> 41B </span>","children":null,"spread":false},{"title":"clayton_v0_2.csv <span style='color:#111;'> 41B </span>","children":null,"spread":false},{"title":"clayton_v0_1.csv <span style='color:#111;'> 41B </span>","children":null,"spread":false},{"title":"rlog_output1.csv <span style='color:#111;'> 41B </span>","children":null,"spread":false},{"title":"frank_v01_2.csv <span style='color:#111;'> 40B </span>","children":null,"spread":false},{"title":"frank_v01_1.csv <span style='color:#111;'> 40B </span>","children":null,"spread":false},{"title":"frank_v0_2.csv <span style='color:#111;'> 39B </span>","children":null,"spread":false},{"title":"frank_v0_1.csv <span style='color:#111;'> 39B </span>","children":null,"spread":false},{"title":"gumbel_v01.csv <span style='color:#111;'> 39B </span>","children":null,"spread":false},{"title":"gumbel_v0.csv <span style='color:#111;'> 38B </span>","children":null,"spread":false},{"title":".gitignore <span style='color:#111;'> 83B </span>","children":null,"spread":false},{"title":"distance2curve.m <span style='color:#111;'> 54.55KB </span>","children":null,"spread":false},{"title":"pwlCopula.m <span style='color:#111;'> 39.73KB </span>","children":null,"spread":false},{"title":"test_depcopularnd.m <span style='color:#111;'> 28.86KB </span>","children":null,"spread":false},{"title":"copulaDensityExperiments.m <span style='color:#111;'> 16.34KB </span>","children":null,"spread":false},{"title":"copMarginalDist.m <span style='color:#111;'> 15.14KB </span>","children":null,"spread":false},{"title":"pwlCopula_D_dim_sparse.m <span style='color:#111;'> 13.02KB </span>","children":null,"spread":false},{"title":"llMask.m <span style='color:#111;'> 12.12KB </span>","children":null,"spread":false},{"title":"test_empcopulapdf.m <span style='color:#111;'> 11.43KB </span>","children":null,"spread":false},{"title":"ecmnmle.m <span style='color:#111;'> 9.80KB </span>","children":null,"spread":false},{"title":"characterizeError.m <span style='color:#111;'> 8.06KB </span>","children":null,"spread":false},{"title":"kde2d.m <span style='color:#111;'> 7.58KB </span>","children":null,"spread":false},{"title":"copmodelsel_helm.m <span style='color:#111;'> 6.85KB </span>","children":null,"spread":false},{"title":"testDetermineOrientation.m <span style='color:#111;'> 6.55KB </span>","children":null,"spread":false},{"title":"test_empcopularnd.m <span style='color:#111;'> 6.19KB </span>","children":null,"spread":false},{"title":"test_empcopulacdf.m <span style='color:#111;'> 6.06KB </span>","children":null,"spread":false},{"title":"emp_copularnd_old1_paper.m <span style='color:#111;'> 5.54KB </span>","children":null,"spread":false},{"title":"test_copulamodelselect.m <span style='color:#111;'> 5.48KB </span>","children":null,"spread":false},{"title":"testStochasticAndFunctionalDependence.m <span style='color:#111;'> 5.43KB </span>","children":null,"spread":false},{"title":"test_empcopulaval.m <span style='color:#111;'> 5.37KB </span>","children":null,"spread":false},{"title":"empcopulapdf.m <span style='color:#111;'> 4.79KB </span>","children":null,"spread":false},{"title":"emp_copularnd_old2_paper.m <span style='color:#111;'> 4.72KB </span>","children":null,"spread":false},{"title":"pobs.m <span style='color:#111;'> 4.71KB </span>","children":null,"spread":false},{"title":"maxcopfamprob.m <span style='color:#111;'> 4.61KB </span>","children":null,"spread":false},{"title":"rvEmpiricalInfo.m <span style='color:#111;'> 4.40KB </span>","children":null,"spread":false},{"title":"claytoncopulapdf.m <span style='color:#111;'> 3.93KB </span>","children":null,"spread":false},{"title":"empcopularnd_old1_paper.m <span style='color:#111;'> 3.90KB </span>","children":null,"spread":false},{"title":"gumbelcopulapdf.m <span style='color:#111;'> 3.80KB </span>","children":null,"spread":false},{"title":"test_discretizeRv.m <span style='color:#111;'> 3.79KB </span>","children":null,"spread":false},{"title":"empcopularnd.m <span style='color:#111;'> 3.76KB </span>","children":null,"spread":false},{"title":"frankcopulapdf.m <span style='color:#111;'> 3.59KB </span>","children":null,"spread":false},{"title":"calcpmf.m <span style='color:#111;'> 3.49KB </span>","children":null,"spread":false},{"title":"marginal_uniformity.m <span style='color:#111;'> 3.44KB </span>","children":null,"spread":false},{"title":"depcopularnd_old.m <span style='color:#111;'> 3.34KB </span>","children":null,"spread":false},{"title":"copulaEdgeTest.m <span style='color:#111;'> 3.31KB </span>","children":null,"spread":false},{"title":"test_maxcopfamprob.m <span style='color:#111;'> 3.31KB </span>","children":null,"spread":false},{"title":"empcopula_old.m <span style='color:#111;'> 3.28KB </span>","children":null,"spread":false},{"title":"ecmnobj.m <span style='color:#111;'> 3.25KB </span>","children":null,"spread":false},{"title":"empcopularnd_old.m <span style='color:#111;'> 3.20KB </span>","children":null,"spread":false},{"title":"polyG.m <span style='color:#111;'> 3.03KB </span>","children":null,"spread":false},{"title":"frankcopularnd.m <span style='color:#111;'> 3.03KB </span>","children":null,"spread":false},{"title":"empcopulaval.m <span style='color:#111;'> 2.99KB </span>","children":null,"spread":false},{"title":"eqdistetest_nonvectorized.m <span style='color:#111;'> 2.97KB </span>","children":null,"spread":false},{"title":"ecmninit.m <span style='color:#111;'> 2.96KB </span>","children":null,"spread":false},{"title":"test_v0v01.m <span style='color:#111;'> 2.95KB </span>","children":null,"spread":false},{"title":"F01Frankrnd.m <span style='color:#111;'> 2.89KB </span>","children":null,"spread":false},{"title":"etstablernd.m <span style='color:#111;'> 2.70KB </span>","children":null,"spread":false},{"title":"gumbelcopularnd.m <span style='color:#111;'> 2.64KB </span>","children":null,"spread":false},{"title":"test_carleybounds.m <span style='color:#111;'> 2.60KB </span>","children":null,"spread":false},{"title":"claytoncopularnd.m <span style='color:#111;'> 2.53KB </span>","children":null,"spread":false},{"title":"startup.m <span style='color:#111;'> 2.45KB </span>","children":null,"spread":false},{"title":"est_empcopulacdfpdf.m <span style='color:#111;'> 2.44KB </span>","children":null,"spread":false},{"title":"test_mvArchimedeanCopulasPDF.m <span style='color:#111;'> 2.39KB </span>","children":null,"spread":false},{"title":"logrnd.m <span style='color:#111;'> 2.35KB </span>","children":null,"spread":false},{"title":"sibuyarnd.m <span style='color:#111;'> 2.31KB </span>","children":null,"spread":false},{"title":"empcopulacdf.m <span style='color:#111;'> 2.28KB </span>","children":null,"spread":false},{"title":"multivariateEnergyDistance.m <span style='color:#111;'> 2.25KB </span>","children":null,"spread":false},{"title":"test_mvArchimedeanCopulasRND.m <span style='color:#111;'> 2.25KB </span>","children":null,"spread":false},{"title":"......","children":null,"spread":false},{"title":"<span style='color:steelblue;'>文件过多，未全部展示</span>","children":null,"spread":false}],"spread":true}]

评论信息

其他资源

免责申明

【只为小站】的资源来自网友分享，仅供学习研究，请务必在下载后24小时内给予删除，不得用于其他任何用途，否则后果自负。基于互联网的特殊性，【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查；无论 【只为小站】 经营者是否已进行审查，用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明

个人信息

下载历史

相关资源标签

热门下载

最新下载