贡纳姆 安装 Gonum套件的核心软件包以纯Go语言编写，并带有一些汇编。 使用go get完成安装。 go get -u gonum.org/v1/gonum/... 受支持的Go版本 Gonum在Linux的（386，amd64和arm64），macOS和Windows（均在amd64上）上使用gc编译器支持和测试。 发布时间表 Gonum模块的发布时间为六个月，与Go版本保持一致。 即：发布Go-1.x时，大约同时发布Gonum-v0.n.0 。 六个月后，发布了Go-1.x+1和Gonum-v0.n+1.0 。 因此，基于当前Go发行时间表的发行时间表为： Gonum-v0.n.0 ：二月 Gonum-v0.n+1.0 ：八月 构建标签 Gonum软件包使用各种构建标记来设置非标准构建条件。 构建Gonum应用程序可以在不知道如何使用这些标签的情况下工作，但是可以在测试期间使用它们并控制汇编和CGO代码的使用。 当前的非内部标签列表如下： 安全-请勿使用汇编程序或不安全的程序 边界-即使在内部调用中也要使用边界检查 cblas —在测试中使用CGO gonum.org

SPSS_Statistics-v19.0win32，经管人必备的统计软件

SQLGitHub的 SQLGitHub-简化GitHub组织管理 介绍 SQLGitHub具有类似于SQL的语法，可让您： 查询有关整个组织的信息。 您可能还认为它是基于GitHub RESTful API之上的更好的，增强的前端层。 安装 安装先决条件 pip install requests prompt_toolkit pygments regex 安装我修补的PyGithub git clone https://github.com/lnishan/PyGithub.git cd PyGithub ./setup.py build sudo ./setup.py install 配置SQLGitHub（可选） 在根目录（与SQLGitHub.py相同的目录）中， 创建和编辑config.py ： token = "your token here" # can be obtained from https://github.com/settings/tokens output = "str" # or "csv", "html" 启动SQLGitHub ./S

使用redmine缺陷管理工具的测试人员注意了，本代码是实现统计redmine的数据（本阶段、本版本、严重等级、指派人员、结构分布情况），并实现自动化发送阶段性测试报告邮件脚本，也有现成的exe程序，大家可是试试（exe是使用内网地址，大家可能会运行失败，这也是保证公司机密不被泄露），如果大家有问题，可以随时私聊我

this book aims at showing the intersection of statistical, logical and relational learning.

Statistics and Machine Learning Toolbox User’s Guide Statistics and Machine Learning Toolbox Release Notes

Introduction to Probability and Statistics 14th Edition，可编辑版本，很好用的。

第七版 Indroduction_to_Mathematica_Statistics.Hogg,McKean,Craig seventh edition.pdf UIUC的 STAT401统计课程教材 Contents Preface ix 1 Probability and Distributions 1 1.1 Introduction................................ 1 1.2 SetTheory ................................ 3 1.3 TheProbabilitySetFunction ...................... 10 1.4 ConditionalProbabilityandIndependence . . . . . . . . . . . . . . . 21 1.5 RandomVariables ............................ 32 1.6 DiscreteRandomVariables ....................... 40 1.6.1 Transformations ......................... 42 1.7 ContinuousRandomVariables...................... 44 1.7.1 Transformations ......................... 46 1.8 ExpectationofaRandomVariable ................... 52 1.9 SomeSpecialExpectations ....................... 57 1.10ImportantInequalities .......................... 68 2 Multivariate Distributions 73 2.1 DistributionsofTwoRandomVariables ................ 73 2.1.1 Expectation............................ 79 2.2 Transformations: Bivariate Random Variables . . . . . . . . . . . . . 84 2.3 Conditional Distributions and Expectations . . . . . . . . . . . . . . 94 2.4 TheCorrelationCoefficient ....................... 102 2.5 IndependentRandomVariables.....................110 2.6 ExtensiontoSeveralRandomVariables . . . . . . . . . . . . . . . . 117 2.6.1 ∗Multivariate Variance-Covariance Matrix . . . . . . . . . . . 123 2.7 Transformations for Several Random Variables . . . . . . . . . . . . 126 2.8 LinearCombinationsofRandomVariables. . . . . . . . . . . . . . . 134 3 Some Special Distributions 139 3.1 TheBinomialandRelatedDistributions . . . . . . . . . . . . . . . . 139 3.2 ThePoissonDistribution ........................ 150 3.3 TheΓ,χ2,andβDistributions ..................... 156 3.4 TheNormalDistribution......................... 168 3.4.1 ContaminatedNormals ..................... 174 v vi Contents 3.5 TheMultivariateNormalDistribution ................. 178 3.5.1 ∗Applications........................... 185 3.6 t-andF-Distributions

解压密码 share.weimo.info Put statistical theories into practice with PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9th . Always a market favorite, this calculus-based book offers a comprehensive introduction to probability and statistics while demonstrating how to apply concepts, models, and methodologies in today's engineering and scientific workplaces. Jay Devore, an award-winning professor and internationally recognized author and statistician, stresses lively examples and engineering activities to drive home the numbers without exhaustive mathematical development and derivations. Many examples, practice problems, sample tests, and simulations based on real data and issues help you build a more intuitive connection to the material. A proven and accurate book, PROBABILITY AND STATISTICS FOR ENGINEERING AND THE SCIENCES, 9th also includes graphics and screen shots from SAS, MINITAB, and Java™ Applets to give you a solid perspective of statistics in action.,解压密码 share.weimo.info

Contents Preface v Typographical Conventions xi 1 Introduction 1 1.1 A Quick Overview of S ....................... 3 1.2 Using S ............................... 5 1.3 An Introductory Session . . . . . ................. 6 1.4 WhatNext? ............................. 12 2 DataManipulation 13 2.1 Objects ............................... 13 2.2 Connections............................. 20 2.3 DataManipulation ......................... 27 2.4 TablesandCross-Classification................... 37 3The S Language 41 3.1 Language Layout . . ........................ 41 3.2 More on S Objects ......................... 44 3.3 ArithmeticalExpressions...................... 47 3.4 CharacterVectorOperations .................... 51 3.5 Formatting and Printing . . . . . . ................. 54 3.6 Calling Conventions for Functions ................. 55 3.7 ModelFormulae........................... 56 3.8 ControlStructures.......................... 58 3.9 ArrayandMatrixOperations.................... 60 3.10 Introduction to Classes and Methods . . . ............. 66 4 Graphics 69 4.1 GraphicsDevices .......................... 71 4.2 Basic Plotting Functions . . . . . ................. 72 viiviii Contents 4.3 EnhancingPlots........................... 77 4.4 FineControlofGraphics ...................... 82 4.5 Trellis Graphics . . . ........................ 89 5 Univariate Statistics 107 5.1 Probability Distributions . . . . . .................107 5.2 Generating Random Data . . . . . .................110 5.3 DataSummaries...........................111 5.4 ClassicalUnivariateStatistics....................115 5.5 RobustSummaries .........................119 5.6 DensityEstimation .........................126 5.7 Bootstrap and Permutation Methods . . . .............133 6 Linear StatisticalModels 139 6.1 AnAnalysisofCovarianceExample................139 6.2 ModelFormulaeandModelMatrices ...............144 6.3 Regression Diagnostics . . . . . . .................151 6.4 SafePrediction ....................