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空間統(tǒng)計學理論:概述:a concise introduction:英文 版權信息
- ISBN：9787576712858
- 條形碼：9787576712858 ; 978-7-5767-1285-8
- 裝幀：平裝-膠訂
- 冊數：暫無
- 重量：暫無
- 所屬分類：>>
空間統(tǒng)計學理論:概述:a concise introduction:英文 內容簡介
本書是一部統(tǒng)計學方面的專著，每章首先介紹理論，其次使用資源R包將其應用于說明性示例中，列出一些練習，*后以參考文獻結尾。本書共分為4章，介紹了網格數據點、單位面積數據點、映射點模式數據、高斯隨機域、平穩(wěn)性概念、協(xié)方差函數的構造、簡單克里格方法、半方差函數、貝葉斯估計、離散隨機域、高斯自回歸模型、馬爾可夫隨機域、歐幾里得空間上的點過程、泊松過程、有限點過程、分層建模等內容。本書適合數學、工程學、統(tǒng)計學研究生參考閱讀。
空間統(tǒng)計學理論:概述:a concise introduction:英文 目錄
Preface Author
CHAPTER 1 Introduction
1.1 GRIDDED DATA
1.2 AREAL UNIT DATA
1.3 MAPPED POINT PATTERN DATA
1.4 PLAN OF THE BOOK
CHAPTER 2 Random field modelling and interpolation
2.1 RANDOM FIELDS
2.2 GAUSSIAN RANDOM FIELDS
2.3 STATIONARITY CONCEPTS
2.4 CONSTRUCTION OF COVARIANCE FUNCTIONS
2.5 PROOF OF BOCHNER'S THEOREM
2.6 THE SEMI-VARIOGRAM
2.7 SIMPLEKRIGING
2.8 BAYES ESTIMATOR
2.9 ORDINARY KRIGING
2.10 UNIVERSAL KRIGING
2.11 WORKED EXAMPLES WITH R
2.12 EXERCISES
2.13 POINTERS TO THE LITERATURE
CHAPTER 3 Models and inference for areal unit data
3.1 DISCRETE RANDOM FIELDS etnefno
3.2 GAUSSIAN AUTOREGRESSION MODELS
3.3 GIBBS STATES
3.4 MARKOV RANDOM FIELDS
3.5 INFERENCE FOR AREAL UNIT MODELS
3.6 MARKOV CHAIN MONTE CARLO SIMULATION
3.7 HIERARCHICAL MODELLING
3.7.1 Image segmentation
3.7.2 Disease mapping
3.7.3 Synthesis
3.8 WORKED EXAMPLES WITH R
3.9 EXERCISES
3.10 POINTERS TO THE LITERATURE
CHAPTER 4 Spatial point processes
4.1 POINT PROCESSES ON EUCLIDEAN SPACES
4.2 THE POISSON PROCESS
4.3 MOMENT MEASURES
4.4 STATIONARITY CONCEPTS AND PRODUCT DENSITIES
4.5 FINITE POINT PROCESSES
4.6 THE PAPANGELOU CONDITIONAL INTENSITY
4.7 MARKOV POINT PROCESSES
4.8 LIKELIHOOD INFERENCE FOR POISSON PROCESSES
4.9 INFERENCE FOR FINITE POINT PROCESSES
4.10 COX PROCESSES
4.10.1 Cluster processes
4.10.2 Log-Gaussian Cox processes
4.10.3 Minimum contrast estimation
4.11 HIERARCHICAL MODELLING
4.12 WORKED EXAMPLES WITH R
4.13 EXERCISES
4.14 POINTERS TO THE LITERATURE
Appendix：Solutions to theoretical exercises
Index
編輯手記
CHAPTER 1 Introduction
1.1 GRIDDED DATA
1.2 AREAL UNIT DATA
1.3 MAPPED POINT PATTERN DATA
1.4 PLAN OF THE BOOK
CHAPTER 2 Random field modelling and interpolation
2.1 RANDOM FIELDS
2.2 GAUSSIAN RANDOM FIELDS
2.3 STATIONARITY CONCEPTS
2.4 CONSTRUCTION OF COVARIANCE FUNCTIONS
2.5 PROOF OF BOCHNER'S THEOREM
2.6 THE SEMI-VARIOGRAM
2.7 SIMPLEKRIGING
2.8 BAYES ESTIMATOR
2.9 ORDINARY KRIGING
2.10 UNIVERSAL KRIGING
2.11 WORKED EXAMPLES WITH R
2.12 EXERCISES
2.13 POINTERS TO THE LITERATURE
CHAPTER 3 Models and inference for areal unit data
3.1 DISCRETE RANDOM FIELDS etnefno
3.2 GAUSSIAN AUTOREGRESSION MODELS
3.3 GIBBS STATES
3.4 MARKOV RANDOM FIELDS
3.5 INFERENCE FOR AREAL UNIT MODELS
3.6 MARKOV CHAIN MONTE CARLO SIMULATION
3.7 HIERARCHICAL MODELLING
3.7.1 Image segmentation
3.7.2 Disease mapping
3.7.3 Synthesis
3.8 WORKED EXAMPLES WITH R
3.9 EXERCISES
3.10 POINTERS TO THE LITERATURE
CHAPTER 4 Spatial point processes
4.1 POINT PROCESSES ON EUCLIDEAN SPACES
4.2 THE POISSON PROCESS
4.3 MOMENT MEASURES
4.4 STATIONARITY CONCEPTS AND PRODUCT DENSITIES
4.5 FINITE POINT PROCESSES
4.6 THE PAPANGELOU CONDITIONAL INTENSITY
4.7 MARKOV POINT PROCESSES
4.8 LIKELIHOOD INFERENCE FOR POISSON PROCESSES
4.9 INFERENCE FOR FINITE POINT PROCESSES
4.10 COX PROCESSES
4.10.1 Cluster processes
4.10.2 Log-Gaussian Cox processes
4.10.3 Minimum contrast estimation
4.11 HIERARCHICAL MODELLING
4.12 WORKED EXAMPLES WITH R
4.13 EXERCISES
4.14 POINTERS TO THE LITERATURE
Appendix：Solutions to theoretical exercises
Index
編輯手記
展開全部
空間統(tǒng)計學理論:概述:a concise introduction:英文 作者簡介
M.N.M.范·利舒特，荷蘭人，荷蘭阿姆斯特丹數學與計算機科學中心（CWI）的高級研究員，并在特溫特大學擔任空間隨機學教授。
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