Topic
Kriging
About: Kriging is a research topic. Over the lifetime, 9100 publications have been published within this topic receiving 257671 citations. The topic is also known as: Gaussian process regression.
Papers published on a yearly basis
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Papers
Book•
1 Jan 1991TL;DR: In this paper, the authors present a survey of statistics for spatial data in the field of geostatistics, including spatial point patterns and point patterns modeling objects, using Lattice Data and spatial models on lattices.
Abstract: Statistics for Spatial Data GEOSTATISTICAL DATA Geostatistics Spatial Prediction and Kriging Applications of Geostatistics Special Topics in Statistics for Spatial Data LATTICE DATA Spatial Models on Lattices Inference for Lattice Models SPATIAL PATTERNS Spatial Point Patterns Modeling Objects References Author Index Subject Index.
9,063 citations
Book•
1 Jan 1973
TL;DR: In this article, a thoroughly revised edition presents important methods in the quantitative analysis of geologic data, such as probability, nonparametric statistics, and Fourier analysis, as well as data analysis methods such as the semivariogram and the process of kriging.
Abstract: From the Publisher:
This thoroughly revised edition presents important methods in the quantitative analysis of geologic data. Retains the basic arrangement of the previous edition but expands sections on probability, nonparametric statistics, and Fourier analysis. Contains revised coverage of eigenvalues and eigenvectors, and new coverage of data analysis methods, such as the semivariogram and the process of kriging.
6,761 citations
Book•
28 Apr 1995
TL;DR: The aim of this book is to provide a history of numerical methods in practice in the context of ecological data collection and its application to Dune meadow data.
Abstract: Ecological data has several special properties: the presence or absence of species on a semi-quantitative abundance scale; non-linear relationships between species and environmental factors; and high inter-correlations among species and among environmental variables. The analysis of such data is important to the interpretation of relationships within plant and animal communities and with their environments. In this corrected version of Data Analysis in Community and Landscape Ecology, without using complex mathematics, the contributors demonstrate the methods that have proven most useful, with examples, exercises and case-studies. Chapters explain in an elementary way powerful data analysis techniques such as logic regression, canonical correspondence analysis, and kriging.
4,481 citations
Book•
7 Apr 1999
TL;DR: In this article, the Intrinsic Model of Order (IMO) is used for structural analysis and nonlinear methods are used for nonlinear models of scale effects and inverse problems.
Abstract: Preliminaries. Structural Analysis. Kriging. Intrinsic Model of Order k. Multivariate Methods. Nonlinear Methods. Conditional Simulations. Scale Effects and Inverse Problems. Appendix. References. Index.
3,639 citations
TL;DR: The gstat S package is introduced, an extension package for the S environments (R, S-Plus) that provides multivariable geostatistical modelling, prediction and simulation, as well as several visualisation functions.
3,019 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2026 | 3 |
| 2025 | 375 |
| 2024 | 625 |
| 2023 | 1,091 |
| 2022 | 1,768 |
| 2021 | 630 |