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1 Introduction
2 Basic Stochastic Processes
2.1 Definitions, 9
2.2 Covariances and Spectra, 10
2.3
2.4 Gibbs Processes, 14
2.5
Poisson and Point Processes, 13
Monte Carlo Methods and Simulation, 16
3 Spatial Sampling
3.1 Sampling Schemes, 19
3.2 Error Variances, 22
3.3 Estimating Sampling Errors, 25
3.4 Optimal Location of Samples, 27
References, 27
4 Smoothing and Interpolation
4.1 Trend Surfaces, 29
4.2 Moving Averages, 36
4.3 Tessellations and Triangulations, 38
4.4 Stochastic Process Prediction, 44
4.5 Contouring, 75
5 Regional and Lattice Data
5.1 Two-Dimensional Spectral Analysis, 79
5.2 Spatial Autoregressions, 88
5.3 Agricultural Field Trials, 95
5.4 Regression and Spatial Autocorrelation, 98
6 Quadrat Counts
6.1 Indices, 102
6.2 Discrete Distributions, 106
6.3 Blocks of Quadrats, 108
6.4 One-Dimensional Examples, 1 12
6.5 Two-Dimensional Examples, 119
7 Field Methods for Point Patterns
7.1 Distance Methods, 131
7.2 Forestry Estimators, 138
7.3 Line Transects, 139
8 Mapped Point Patterns
8.1 Basic Parameters, 149
8.2 Nearest-Neighbor Methods, 152
8.3 Second Moments, 158
8.4 Models, 164
8.5 Comparative Studies, 168
8.6 Examples, 169
9 Image Analysis and Stereology
9.1 Random Set Theory, 192
9.2 Basic Quantities, 199
9.3 Stereological Sampling, 204
9.4 Size Distributions, 206
References, 212
Bibliography
spatial stat.rar
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