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这本书在KOOP的Bayesian Econometrics当中经常提到，最近得到这本书，也将其上传。格式为网页形式，看起来不很方便，如有人能将它转化成PDF就好了。说明在先，实在需要的就下载吧。
title : Intermediate Statistics and Econometrics : A
Comparative Approach
author : Poirier, Dale J.
publisher : MIT Press
isbn10 | asin :
print isbn13 : 9780262161497
ebook isbn13 : 9780585134864
language : English
subject
Economics--Statistical methods, Econometrics,
Mathematical statistics.
publication date : 1995
lcc : HB137.P645 1995eb
ddc : 330/.01/5195
subject :
Economics--Statistical
Contents
Words of Wisdom xi
Preface xiii
1 Introduction
1.1 The Origin of Econometrics 1
1.2 Realism Versus Instrumentalism 1
1.3 The Shuttle Disaster 4
2 Basic Concepts
2.1 Probability 9
2.2 Random Variables 29
2.3 Univariate Mathematical Expectation 36
2.4 Joint and Conditional Distributions 43
2.5 Stochastic Independence 52
2.6 Multivariate Mathematical Expectation 55
2.7 Population Regression and Partial Correlation 64
2.8 Inequalities 76
3 Special Distributions 81
3.2 Discrete Univariate Distributions 81
3.3 Continuous Univariate Distributions 93
3.4 Multivariate Distributions I 117
3.5 Multivariate Distributions II 136
4 Distributions of Functions of Random Variables 143
4.1 Introduction 143
4.2 Cumulative Distribution Function Technique 143
4.3 Moment Generating Function Technique 147
4.4 Change-of-Variable Technique 149
4.5 Quadratic-Form Technique 155
5 Sampling Theory
5.1 Basic Concepts 165
5.2 Statistics and Sample Moments 168
5.3 Sampling Distributions 176
5.4 Order Statistics 185
151
185
5.5 Stochastic Convergence
5.6 Laws of Large Numbers 199
5.7 Central Limit Theorems 201
5.8 Subjectivist View of Sampling 210
6 Estimation
6.1 Likelihood and Sufficiency 219
6.2 Likelihood and Stopping Rule Principles 226
6.3 Sampling Properties of Point Estimators in Finite Samples 233
6.4 Sampling Properties of Point Estimators in Large Samples 250
6.5 An Overview of Frequentist Point Estimation 259
6.6 Classical Point Estimation Methods 271
6.7 Bayesian Point Estimation 288
6.8 Choice of Prior and Bayesian Sensitivity Analysis 318
6.9 Interval Estimation 334
6.10 Reflections on Conditioning 343
7 Hypothesis Testing
7.1 Introduction 351
7.2 Sampling Theory Approach 354
7.3 Asymptotic Tests 367
376
7.4 Bayesian Posterior Odds
7.5 P-values 396
7.6 Postscript 400
8 Prediction
8.1 Introduction 405
8.2 The Simplest Case: Known Parameters 411
8.3 Structural Modelling 418
8.4 Predictive Likelihood 425
8.5 Classical Point and Interval Prediction 429
8.6 Bayesian Point and Interval Prediction 432
8.7 Combination of Forecasts 439
9 The Linear Regression Model
9.1 A Tale of Two Regressions 445
9.2 Classical Estimation in Multiple Linear Normal Regression 460
9.3 Estimation Subject to Exact Restrictions on Regression Coefficients 482
9.4 Distribution Theory for Classical Estimation 490
9.5 Confidence Intervals 494
498
9.6 Classical Hypothesis Testing
9.7 Dummy Variables 509
9.8 Pretest Estimators 519
9.9 Bayesian Estimation in Multiple Linear Normal Regression 524
9.10 Bayesian Hypothesis Testing 540
9.11 Prediction 551
9.12 Goodness-of-Fit 559
9.13 Sample Partial Correlation 563
9.14 Multicollinearity 567
10 Other Windows on the Word
10.1 Introduction 585
10.2 The Initial Window 586
10.3 Examples of Larger Words 590
10.4 Pragmatic Principles of Model Building 601
10.5 Statistical Framework 602
10.6 Pure Significance Tests 607
10.7 Diagnostic Checking of the Maintained Hypothesis 609
613
10.8 Data-Instigated Hypotheses
10.9 Reconciliation 615
Appendix A
Matrix Algebra Review I
A. 1 Elementary Definitions 619
A.2 Vector Spaces 621
A.3 Determinants and Ranks 624
A.4 Inverses 626
A.5 Systems of Linear Equations and Generalized Inverses 629
A.6 Idempotent Matrices 633
A.7 Characteristic Roots and Vectors 634
A.8 Quadratic Forms and Definite Matrices 638
Appendix B
Matrix Algebra Review H
B.1 Kronecker Products 645
B.2 Vectorization of Matrices 646
B.3 Matrix Differentiation 649
Appendix C
Computation
C. 1 Maximization 653
654
C.2 Monte Carlo Integration
C.3 Gibbs sampling 659
Appendix D
Statistical Tables
D. 1 Cumulative Normal Distribution 661
D.2 Cumulative Chi-Squared Distribution 662
D.3 Cumulative F-Distribution 663
D.4 Cumulative Student t-Distribution 666
References 667
Author Index 699
Subject Index 705
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