作者：（美）雷奥奇
页数：660
出版社：机械工业出版社
出版日期：2018
ISBN：9787111109457
电子书格式：pdf/epub/txt
内容简介
雷奥奇·卡塞拉、罗杰L.贝耶编著的《统计推断(英文版原书第2版)》从概率论的基础开始，通过例子与习题的旁征博引，引进了大量近代统计处理的新技术和一些国内同类教材中不能见而广为使用的分布。其内容包括工科概率论入门、经典统计和现代统计的基础，又加进了不少近代统计中数据处理的实用方法和思想，例如：Bootstrap再抽样法、刀切（Jackknife）估计、EM算法、Logistic回归、稳健（Robust）回归、Markov链、Monte Carlo方法等。它的统计内容与国内流行的教材相比，理论较深，模型较多，案例的涉及面要广，理论的应用面要丰富，统计思想的阐述与算法更为具体。《统计推断(英文版原书第2版)》可作为工科、管理类学科专业本科生、研究生的教材或参考书，也可供教师、工程技术人员自学之用。
本书特色
本书并不假定在任何概率论的先修知识。通过正文与习题旁征博引，引进了大量近代统计处理的新技术和一些国内同类教材中不能见而广为使用的分布。其内容包括工科概率论入门又包括了经典统计和现代统计的基础部分。其理论较为现代化、难度适中，覆盖面远比国内教材大，而在体系结构与内容安排上富于新意。本书可以作为工科、管理类学科专业本科生、研究生教材，也可供教师、工程技术人员自学之用。
目录
PROBABILITY THEORY
1.1 Set Theory
1.2 Basics of Probability Theory
1.3 Conditional Probability and
Independence
1.4 Random Variables
1.5 Distribution Functions
1.6 Density and Mass Functions
1.7 Exercises
1.8 Miscellanea
2
TRANSFORMATIONS AND EXPECTATIONS
2.1 Distributions of Functions of
a Random Variable
2.2 Expected Values
2.3 Moments and Moment Generating
Functions
2.4 Differentiating Under an
Integral Sign
2.5 Exercises
2.6
Miscellanea
3
COMMON FAMILIES OF DISTRIBUTIONS
3.1 Introduction
3.2 Discrete Distributions
3.3 Continuous Distributions
3.4 Exponential Families
3.5 Location and Scale Families
3.6 Inequalities and Identities
3.7 Exercises
3.8 Miscellanea
4
MULTIPLE RANDOM VARIABLES
4.1 Joint and Marginal
Distributions
4.2 Conditional Distributions and
Independence
4.3 Bivariate Transformations
4.4 Hierarchical Models and
Mixture Distributions
4.5 Covariance and Correlation
4.6 Multivariate Distributions
4.7 Inequalities
4.8 Exercises
4.9 Miscellanea
5
PROPERTIES OF A RANDOM SAMPLE
5.1 Basic Concepts of Random
Samples
5.2 Sums of Random Variables from
a Random Sample
5.3 Sampling from the Normal
Distribution
5.4 Order Statistics
5.5 Convergence Concepts
5.6 Generating a Random Sample
5.7 Exercises
5.8 Miscellanea
6
PRINCIPLES OF DATA REDUCTION
6.1 Introduction
6.2 The Sufficiency Principle
6.3 The Likelihood Principle
6.4 The Equivariance Principle
6.5 Exercises
6.6 Miscellanea
7
Point Estimation
7.1 Introduction
7.2 Methods of Finding Estimators
7.3 Methods of Evaluating
Estimators
7.4
Exercises
7.5 Miscellanea
8
HYPOTHESIS TESTING
8.1 Introduction
8.2 Methods of Finding Tests
8.3 Methods of Evaluating Tests
8.4 Exercises
8.5 Miscellanca
9
INTERVAL ESTIMATION
9.1 Introduction
9.2 Methods of Finding Interval
Estimators
9.3 Methods of Evaluating
Interval Estimators
9.4 Exercises
9.5 Miscellanea
10
ASYMPTOTIC EVALUATIONS
10.1 Point Estimation
10.2 Robustness
10.3 Hypothesis Testing
10.4 Interval Estimation
10.5 Exercises
106 Miscellanea
11
ANALYSIS OF VARIANCE AND REGRESSION
11.1 Introduction
11.2 Oneway Analysis of Variance
11.3 Simple Linear Regression
11.4 Exercises
11.5 Miscellanea
12
Regression Models
12.1 Introduction
12.2 Regression with Errors in
Variables
12.3 Logistic Regression
12.4 Robust Regression
12.5 Exercises
12.6 Miscellanea
