《數理統計學導論》是2012年機械工業出版社出版的圖書，作者是霍格、Joseoh W.McKean 、Allen T.Craig。
基本介紹
- 中文名：數理統計學導論
- 作者：霍格(Robert V.Hogg)、 （美國）Joseoh W.McKean 、（美國）Allen T.Craig
- 出版社：機械工業出版社
- 出版時間：2012年6月1日
- 頁數：694 頁
- 開本：16 開
- ISBN：9787111385806
- 外文名：Introduction to Mathematical Statistics(Seventh Edition)
- 類型：科學與自然
- 語種：英語
內容簡介,圖書目錄,作者簡介,名人推薦,編輯推薦,
內容簡介
《數理統計學導論(英文版·第7版)》與前幾版相比，本版引入了最近新的數理統計發展成果，採用現在流行的R軟體進行統計計算和推斷。《數理統計學導論(英文版·第7版)》特色全面覆蓋估計和檢驗中的經典統計推斷過程。深入討論充分性和檢驗理論，包括一致最大功效檢驗和似然比檢驗。提供豐富的實例和練習，便於讀者理解和鞏固相關知識。附錄B中給出更多的R函式實例，幫助讀者了解使用R進行統計計算與模擬。
《數理統計學導論(英文版·第7版)》是數理統計方面的一本經典教材，自1959年出版以來，廣受讀者好評，並被眾多院校選為教材，如布朗大學、喬治華盛頓大學等。第7版延續了前幾版的一貫風格，清晰而全面地闡述了數理統計的基本理論，並且為了讓讀者更好地理解數理統計，還提供了豐富的例子和一些重要的背景材料。
圖書目錄
Preface
1 Probahility and Distributions
1.1 Introduction
1.2 Set Theory
1.3 The Probability Set Function
1.4 Conditional Probability and Independence
1.5 Random Variables
1.6 Discrete Random Variables
1.6.1 Transformations
1.7 Continuous Random Variables
1.7.1 Transformations
1.8 Expectation of a Random Variable
1.9 Some Special Expectations
1.10 Important Inequalities
2 Multivariate Distributions
2.1 Distributions of Two Random Variables
2.1.1 Expectation
2.2 Transformations: Bivariate Random Variables
2.3 Conditional Distributions and Expectations
2.4 The Correlation Coefficient
2.5 Independent Random Variables
2.6 Extension to Several Random Variables
2.6.1*Multivariate Variance-Covariance Matrix
2.7 Transformations for Several Random Variables
2.8 Linear Combinations of Random Variables
3 Some Special Distributions
3.1 The Binomial and Related Distributions
3.2 The Poisson Distribution
3.3 The Г,α2,and β Distributions
3.4 The Normal Distribution
3.4.1 Contanunated Normals
3.5 The Multivariate Normal Distribution
3.5.1*Applications
3.6 t-and F-Distributions
3.6.1 The t-distribution
3.6.2 The F-distribution
3.6.3 Student's Theorem
3.7 Mixture Distributions
4 Some Elementary Statistical Inferences
4.1 Sampling and Statistics
4.1.1 Histogram Estimates of pmfs and pdfs
4.2 Confidence Intervals
4.2.1 Confidence Intervals for Difference in Means
4.2.2 Confidence Interval for Difference in Proportions
4.3 Confidence Intervals for Parameters of Discrete Distributions
4.4 Order Statistics
4.4.1 Quantiles
4.4.2 Confidence Intervals for Quantiles
4.5 Introduction to Hypothesis Testing
4.6 Additional Comments About Statistical Tests
4.7 Chi-Square Tests
4.8 The Method of Monte Carlo
4.8.1 Accept-Reject Generation Algorithm
4.9 Bootstrap Procedures
4.9.1 Percentile Bootstrap Confidence Intervals
4.9.2 Bootstrap Testing Procedures
4.10*Tolerance Limits for Distributions
5 Consistency and Limiting Distributions
5.1 Convergencein Probability
5.2 Convergencein Distribution
5.2.1 Bounded in Probability
5.2.2 △-Method
5.2.3 Moment Generating Function Technique
5.3 Central Limit Theorem
5.4*Extensions to Multivariate Distributions
6 Maximum Likelihood Methods
6.1 Maximum Likelihood Estimation
6.2 Rao-Cramér Lower Bound and Efficiency
6.3 Maximum Likelihood Tests
6.4 Multiparameter Case: Estimation
6.5 Multiparameter Case: Testing
6.6 The EM Algorithm
7 Sufficiency
7.1 Measures of Quality of Estimators
7.2 A Sufficient Statistic for a Parameter
7.3 Properties of a Sufficient Statistic
7.4 Completeness and Uniqueness
7.5 The Exponential Class of Distributions
7.6 Functions of a Parameter
7.7 The Case of Several Parameters
7.8 Minimal Sufficiency and Ancillary Statistics
7.9 Sufficiency,Completeness,and Independence
8 Optimal Tests of Hypotheses
8.1 Most Powerful Tests
8.2 Uniformly Most Powerful Tests
8.3 Likelihood Ratio Tests
8.4 The Sequential Probability Ratio Test
8.5 Minimax and Classification Procedures
8.5.1 Minimax Procedures
8.5.2 Classification
9 Inferences About Normal Models
9.1 Quadratic Forms
9.2 One-Way ANOVA
9.3 Noncentral x2 and F-Distributions
9.4 Multiple Comparisons
9.5 The Analysis of Variance
9.6 A Regression Problem
9.7 A Test of Independence
9.8 The Distributions of Certain Quadratic Forms
9.9 The Independence of Certain Quadratic Forms
10 Nonparametric and Robust Statistics
10.1 Location Models
10.2 Sample Median and the Sign Test
10.2.1 Asymptotic Relative Efficiency
10.2.2 Estimating Equations Based on the Sign Test
10.2.3 Confidence Interval for the Median
10.3 Signed-Rank Wilcoxon
10.3.1 Asymptotic Relative Efficiency
10.3.2 Estimating Equations Based on Signed-Rank Wilcoxon
10.3.3 Confidence Interval for the Median
10.4 Mann-Whitney-Wilcoxon Procedure
10.4.1 Asymptotic Relative Efficiency
10.4.2 Estimating Equations Based on the Mann-Whitney-Wilcoxon
10.4.3 Confidence Interval for the Shift Parameter △
10.5 General Rank Scores
10.5.1 Efficacy
10.5.2 Estimating Equations Based on General Scores
10.5.3 Optimization:Best Estimates
10.6 Adaptive Procedures
10.7 Simple Linear Model
10.8 Measures of Association
10.8.1 Kendall's Τ
10.8.2 Spearman's Rho
10.9 Robust Concepts
10.9.1 Location Model
10.9.2 Linear Model
11 Bayesian Statistics
11.1 Subjective Probability
11.2 Bayesian Procedures
11.2.1 Prior and Posterior Distributions
11.2.2 Bayesian Point Estimation
11.2.3 Bayesian Interval Estimation
11.2.4 Bayesian Testing Procedures
11.2.5 Bayesian Sequential Procedures
11.3 More Bayesian Tenrminology and Ideas
11.4 Gibbs Sampler
11.5 Modern Bayesian Methods
11.5.1 Empirical Bayes
A Mathematical Comments
A.1 Regularity Conditions
A.2 Sequences
B R Functions
C Tables of Distributions
D Lists of Common Distributions
E References
F Answers to Selected Exerases
Index
作者簡介
作者：（美國）霍格（Robert V.Hogg） （美國）Joseoh W.McKean （美國）Allen T.Craig
霍格（Robert V.Hogg），愛荷華大學統計與精算科學系教授，自1948年開始任教於愛荷華大學，在此從事教學和管理工作50多年，並幫助籌建了統計與精算科學系。他曾擔任美國統計協會（ASA）主席，獲得過包括美國數學協會傑出教育獎在內的多項教學獎。
Joseph W.McKean，西密西根大學統計系教授，ASA會士。他線上性、非線性、混合模型的穩健非參數處理方面已發表多篇論文，主要講授統計學、機率論、統計方法、非參數理論等課程。
Allen T.Craig，愛荷華大學教授，已於1970年退休。他曾擔任美國數理統計學會（IMS）第一任秘書長，發起並參與了本書的撰寫工作。
名人推薦
“該書寫作風格極其清晰，就更高等內容的套用而言，我沒有任何質疑。書中內容表述專業而現代，假如我有機會再次講授數理統計學，我會毫不猶豫使用它，同時推薦給我的同事們。”
——Walter Freiberger，布朗大學
編輯推薦
在努力降低引進教材售價方面，高等教育出版社做了大量和細緻的工作，這套引進的教材體現了一定的權威性、系統性、先進性和經濟性等特點。《數理統計學導論》(第5版影印版)是系列之一！
