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MixedVineToolbox-master

于 2020-10-03 发布

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下载积分: 1 下载次数: 3

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代码说明：

说明：混合藤Copula工具箱 A. Onken and S. Panzeri (2016). Mixed vine copulas as joint models of spike counts and local field potentials. In D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon and R. Garnett, editors, Advances in Neural Information Processing Systems 29 (NIPS 2016), pages 1325-333.(Mixed-Vine Copula Toolbox A. Onken and S. Panzeri (2016). Mixed vine copulas as joint models of spike counts and local field potentials. In D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon and R. Garnett, editors, Advances in Neural Information Processing Systems 29 (NIPS 2016), pages 1325-333.)

文件列表：

MixedVineToolbox-master, 0 , 2017-07-15
MixedVineToolbox-master\LICENSE, 35147 , 2017-07-15
MixedVineToolbox-master\README.md, 3629 , 2017-07-15
MixedVineToolbox-master\copulaccdf.m, 4893 , 2017-07-15
MixedVineToolbox-master\copulaccdfinv.m, 4936 , 2017-07-15
MixedVineToolbox-master\copulacdf.m, 4066 , 2017-07-15
MixedVineToolbox-master\copulafit.m, 2676 , 2017-07-15
MixedVineToolbox-master\copulapdf.m, 4636 , 2017-07-15
MixedVineToolbox-master\copularnd.m, 1922 , 2017-07-15
MixedVineToolbox-master\demo.m, 6841 , 2017-07-15
MixedVineToolbox-master\margincdf.m, 2256 , 2017-07-15
MixedVineToolbox-master\marginfit.m, 3045 , 2017-07-15
MixedVineToolbox-master\margininv.m, 2282 , 2017-07-15
MixedVineToolbox-master\marginpdf.m, 2239 , 2017-07-15
MixedVineToolbox-master\mixedgaussfit.m, 6103 , 2017-07-15
MixedVineToolbox-master\mixedvineentropy.m, 3618 , 2017-07-15
MixedVineToolbox-master\mixedvinefit.m, 8040 , 2017-07-15
MixedVineToolbox-master\mixedvineinfo.m, 3753 , 2017-07-15
MixedVineToolbox-master\mixedvinepdf.m, 6866 , 2017-07-15
MixedVineToolbox-master\mixedvinernd.m, 2966 , 2017-07-15

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MixedVineToolbox-master
说明：混合藤Copula工具箱 A. Onken and S. Panzeri (2016). Mixed vine copulas as joint models of spike counts and local field potentials. In D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon and R. Garnett, editors, Advances in Neural Information Processing Systems 29 (NIPS 2016), pages 1325-333.(Mixed-Vine Copula Toolbox A. Onken and S. Panzeri (2016). Mixed vine copulas as joint models of spike counts and local field potentials. In D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon and R. Garnett, editors, Advances in Neural Information Processing Systems 29 (NIPS 2016), pages 1325-333.)

2020-10-03 11:03:13下载

积分：1
削峰填谷算法
说明：粒子群削峰填谷算法,随机搜索算法，有记忆特性(Particle swarm peak clipping valley filling algorithm)

2020-05-16 20:42:41下载

积分：1
DEA模型
说明：经济学中常用的评价指标模型DEA打包成了函数的形式。(DEA, a commonly used evaluation index model in economics, is packaged in the form of function.)

2020-11-17 22:33:13下载

积分：1
构造均匀设计方法
说明： method1_glp.m是好格子点法构造均匀设计，method2_pglp.m是方幂好格子点法构造均匀设计，适用于试验点较多的情况(good lattice points method to construct uniform design)

2020-02-23 12:04:03下载

积分：1
Spillover_updated
说明：此代码可计算Diebold&Yilmaz 溢出指数(The Diebold-Yilmaz Spillover index can be calculated by this code.)

2021-03-28 11:29:11下载

积分：1
灰色预测模型GM（1-N）
说明：灰色预测模型GM（1，N），可以多因素分析，可对未来数据进行预测。程序可直接运行，可以更换数据。预测未来数据时，只需修改T值，以及因变量数据；否则T=0即可。例如，预测未来2个数据，T=2. 输入数据：因变量x1为400.因变量x2为50；因变量x1为450.因变量x2为90。(The grey prediction model GM (1, n) can analyze many factors and predict the future data. The program can run directly and change data. When predicting future data, only the T value and dependent variable data need to be modified; otherwise, t = 0. For example, predict 2 data in the future, t = 2 Input data: the dependent variable X1 is 400, the dependent variable X2 is 50, the dependent variable X1 is 450, and the dependent variable X2 is 90.)

2020-01-04 21:01:43下载

积分：1
小波神经网络
说明：一些基础的小波神经网络用于基础的分类代码，不是很复杂(Some basic wavelet neural networks are used for basic classification codes, which are not very complicated)

2020-08-13 14:28:11下载

积分：1
GeneralStats
说明：一般分析统计量计算，包含平均数，中位数，众数，分位数，方差，标准差，极差，偏度，峰度等统计量计算方法(Calculation of general analysis statistics, including statistics calculation methods such as mean, median, mode, quantile, variance, standard deviation, range, skewness, kurtosis, etc)

2020-06-27 16:54:08下载

积分：1
相空间重构
说明：能够在MATLAB中进行相空间重构辅助时间序列分析，亲测可用(Be able to reconstruct phase space in MATLAB)

2020-03-06 09:31:15下载

积分：1
网络流量在线分析系统的设计与实现
（1）实时抓取网络数据。（2）网络协议分析与显示。（3）将网络数据包聚合成数据流，以源IP、目的IP、源端口、目的端口及协议等五元组的形式存储。（4）计算并显示固定时间间隔内网络连接（双向流）的统计量（如上行与下行的数据包数目，上行与下行的数据

2022-05-28 23:40:12下载

积分：1

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24今日下载