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【matlab】 MultiStatis DL : 0: 多元统计分析的教程。多因素方差分析。图形显示。函数的使用-Multivariate statistical analysis of the tutorial. Multi-factor analysis of variance. Graphical display. Function of the use of
Update : 2024-05-05 Size : 18432 Publisher : 赵少凯
【matlab】 nwaydever3.1 DL : 0: 多元统计分析是一种应用非常广泛的数据处理方法，这是一个运行在MATLAB环境下的多向数据统计分析处理方法的程序，实现最新的多向统计处理运算。-Multivariate statistical analysis is a widely used data processing methods, this is a run on MATLAB environment to the many treatment methods of statistical analysis procedures, the latest of many to achieve statistical processing algorithms.
Update : 2024-05-05 Size : 4268032 Publisher : 李辉
【Windows Develop】 Commonly_used_meteorologica_package DL : 0: 气象保障常用软件包:本书分为10章，包括客观分析、诊断分析、多元统计分析、主分量分析、自适应统计天气预报方法、时间序列分析、谱分析、人工神经网络天气预报方法、灰色系统及气象绘图软件等内容。 Fortran代码写在word文档中。-Commonly used meteorological package: This book is divided into 10 chapters, including an objective analysis, diagnostic analysis, multivariate statistical analysis, principal component analysis, adaptive statistical weather forecasting methods, time series analysis, spectral analysis, artificial neural network forecast method, the gray systems and meteorological elements, such as mapping software. Fortran code written on the word document.
Update : 2024-05-05 Size : 212992 Publisher : 王哲
【Embeded-SCM Develop】 LABVIEW DL : 0: 多元线性回归分析是一种重要的数据处理方法, 借助图形化的虚拟仪器开发平台LabVIEW 可开发出集数据剔错、模型构建、统计检验、区间估计与预测等功能为一体的多元线性回归的可视化数据处理系统。系统构建方法新颖和稳健, 通用性和适应性强, 可方便地与数据采集整合使用, 又可单独应用, 具有广泛应用价值。文章对系统的构建与设计作了阐述, 给出了主要的实现程序。-Abstr act:The multivariate linear regression analysis is an important data processing method. The visual data processing system of the multivariate linear regression has been developed by using graphic virtual instrument engineering workbench- LabVIEW, which collects the functions of inordinate data elimination, model constructing, statistic test, interval estimate and prediction. The constructing method of the system is new and sane, and its versatility and adaptability are good. The software can be integrated with the data acquisition conveniently, and can also be applied alone and it is of extensive application value. The article describes the construction and the design of the system and gives the main realizing program. Key words:LabVIEW, multivar iate linear r egr ession, data processing, system design
Update : 2024-05-05 Size : 1319936 Publisher : 张平
【Software Engineering】 Discriminantanalysisandclusteranalysis DL : 0: 本文档包括了对软件中用到的多元统计分析中判别分析与聚类分析的主要方法(包括距离判别分析,费希尔判别分析,贝叶斯判别分析,逐步判别分析及聚类分析)原理及在本软件中使用的基本方法与设计流程图进行了详尽的阐释,在通过本文档的阅读对软件有一个总体的了解后再确定您要使用的分析方法-This document includes the software used in multivariate statistical analysis of discriminant analysis and cluster analysis of the main methods (including distance discriminant analysis, Fisher discriminant analysis, Bayesian discriminant analysis, stepwise discriminant analysis and cluster analysis) the principle of and in the software used in the design of the basic methods and a detailed flow chart to explain, in reading through this document one of the software and then to determine the overall understanding of the analysis you want to use methods
Update : 2024-05-05 Size : 1938432 Publisher : youyi
【Embeded-SCM Develop】 duoyuantongji DL : 0: sas的多元统计应用上、有关sas的应用-Application of Multivariate Statistical sas, the application of the sas
Update : 2024-05-05 Size : 40960 Publisher : 于其
【Other】 duoyuantongjixia DL : 0: sas的程序有关多元统计下的很有用-sas multivariate statistical procedures of the very useful
Update : 2024-05-05 Size : 153600 Publisher : 于其
【Other】 GraphicalModelsAndExponentialFamilies DL : 0: 本书介绍了一些常用的图论模型以及图论在通信，统计，优化，图像处理，机器学习等方面的应用-The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate statistical models. Graphical models have become a focus of research in many statistical, computational and mathematical fields, including bioinformatics, communication theory, statistical physics, combinatorial optimization, signal and image processing, information retrieval and statistical machine learning. Many problems that arise in specific instances — including the key problems of computing marginals and modes of probability distributions — are best studied in the general setting. Working with exponential family representations, and exploiting the conjugate duality between the cumulant function and the entropy for exponential families, we develop general variational representations of the problems of computing likelihoods, marginal probabilities and most probable configurations. We describe how
Update : 2024-05-05 Size : 1815552 Publisher : 万毅
【matlab】 mmvn_toolkit DL : 0: A toolkit for Gaussian mixtures. flexible tools for: Generating univariate, multivariate, or mixtures of gaussians Interactive viewing tools allows viewing of multidimensional data and models. Initialize models, add and remove dimensions or clusters and inspect the fit in real-time. Also includes tools to subset the data using model-based (pseudo-)metrics.-A toolkit for Gaussian mixtures. flexible tools for: Generating univariate, multivariate, or mixtures of gaussians Interactive viewing tools allows viewing of multidimensional data and models. Initialize models, add and remove dimensions or clusters and inspect the fit in real-time. Also includes tools to subset the data using model-based (pseudo-)metrics.
Update : 2024-05-05 Size : 63488 Publisher : tra ba huy
【matlab】 groebner DL : 0: manipulate and solve systems of multivariate polynomial equations by computing the groebner basis-manipulate and solve systems of multivariate polynomial equations by computing the groebner basis
Update : 2024-05-05 Size : 9216 Publisher : xiaoni
【Other】 mvapdf.bkp DL : 0: 多元統計學的分析應用及實用繪圖，大學中高級教程-Applied Multivariate Statistical Analysis
Update : 2024-05-05 Size : 4013056 Publisher : Andrea
【Mathimatics-Numerical algorithms】 mcr_101_m7 DL : 0: multivariate curve regression code: using nmf, pca etc
Update : 2024-05-05 Size : 99328 Publisher : 吴彬麟
【File Operate】 Roystest DL : 0: ROYSTEST. Royston s Multivariate Normality Test. This file describe the Royston s multivariate normality test. ------------------------------------------------------------- Created by A. Trujillo-Ortiz, R. Hernandez-Walls, K. Barba-Rojo, and L. Cupul-Magana Facultad de Ciencias Marinas Universidad Autonoma de Baja California Apdo. Postal 453 Ensenada, Baja California Mexico. atrujo@uabc.mx Copyr-ROYSTEST. Royston s Multivariate Normality Test. This file describe the Royston s multivariate normality test. ------------------------------------------------------------- Created by A. Trujillo-Ortiz, R. Hernandez-Walls, K. Barba-Rojo, and L. Cupul-Magana Facultad de Ciencias Marinas Universidad Autonoma de Baja California Apdo. Postal 453 Ensenada, Baja California Mexico. atrujo@uabc.mx Copyr
Update : 2024-05-05 Size : 6144 Publisher : le thanh tan
【Other】 AppliedMultivariateStatisticalAnalysis DL : 0: Applied Multivariate Statistical Analysis(Wolfgang Hardle,Leopold Simar)
Update : 2024-05-05 Size : 3887104 Publisher : wjj
【Other】 svm_perf.tar DL : 0: SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping h: X --> Y using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel. -SVMstruct is a Support Vector Machine (SVM) algorithm for predicting multivariate or structured outputs. It performs supervised learning by approximating a mapping h: X--> Y using labeled training examples (x1,y1), ..., (xn,yn). Unlike regular SVMs, however, which consider only univariate predictions like in classification and regression, SVMstruct can predict complex objects y like trees, sequences, or sets. Examples of problems with complex outputs are natural language parsing, sequence alignment in protein homology detection, and markov models for part-of-speech tagging. The SVMstruct algorithm can also be used for linear-time training of binary and multi-class SVMs under the linear kernel.
Update : 2024-05-05 Size : 109568 Publisher : jon
【Windows Develop】 KRLS DL : 0: Multivariate Online Anomaly Detection Using Kernel Recursive Least Squares
Update : 2024-05-05 Size : 3072 Publisher : 钱叶魁
【Algorithm】 Matlabcodes-RobustPCA DL : 0: Matlab codes for Robust PCA multivariate control chart-Robust PCA multivariate control chart mainly consists two steps: Step1 Calculates the robust mean and the robust covariance of original dataset using the minimum covariance determinant (MCD). In MCD technique, finding a subset containing half of the data such that its covariance matrix has the lowest determinant, then using this subset to calculate the robust mean and the robust covariance matrix (Hubert, Rousseeuw, & Branden, 2005) Step2 Standardize data using robust mean and robust standard deviation from Step1. Apply PCA analysis, calculate the principalcomponent score matrix Y=ZA, where Z is the robust standardized data matrix, and A is p*p matrix of eigenvectors (also called principalcomponents)
Update : 2024-05-05 Size : 1024 Publisher : Jianxin Zhang
【AI-NN-PR】 code DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2024-05-05 Size : 167936 Publisher : Binh
【File Format】 EM DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2024-05-05 Size : 723968 Publisher : Binh
【File Format】 lect26-em DL : 0: EM algorithm for adaptive multivariate Gaussian mixtures
Update : 2024-05-05 Size : 237568 Publisher : Binh

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