Results 11 to 20 of about 9,408 (217)
On the classification error rates in terms of semivariograms for Gaussian universal kriging models
Lithuanian Journal of Statistics, 2021 Bayes multiclass classification of spatial Gaussian data following the universal kriging model is considered. The closed-form expressions for the maximum likelihood (ML) estimator of regression parameters and the actual error rate (AER) in terms of ...
Kęstutis Dučinskas, Lina Dreižienė
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Jack knifing for semivariogram validation [PDF]
Bragantia, 2010 The semivariogram function fitting is the most important aspect of geostatistics and because of this the model chosen must be validated. Jack knifing may be one the most efficient ways for this validation purpose. The objective of this study was to show the use of the jack knifing technique to validate geostatistical hypothesis and semivariogram models.
Vieira, Sidney Rosa +2 more
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Multiscale Soil Investigations: Physical Concepts And Mathematical Techniques [PDF]
, 2008 Soil variability has often been considered to be composed of “functional” (explained) variations plus random fl uctuations or noise. However, the distinction between these two components is scale dependent because increasing the scale of ...
A. M. Tarquis +31 more
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Semivariogram calculation optimization for object-oriented image classification
Modelling in Science Education and Learning, 2011 In this paper we propose and evaluate different mathematical parameters extracted from the experimental semivariogram for land use/land cover classification using high-resolution images and cadastral mapping limits for the definition of the objects of ...
A. Balaguer-Beser +3 more
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Spatial variability of soil properties and soil erodibility in the Alqueva reservoir watershed [PDF]
, 2015 The aim of this work is to investigate how the spatial variability of soil properties and soil erodibility (K factor) were affected by the changes in land use allowed by irrigation with water from a reservoir in a semiarid area.
Andrade, R. +4 more
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Statistical Modeling of Spatial Extremes [PDF]
, 2012 The areal modeling of the extremes of a natural process such as rainfall or temperature is important in environmental statistics; for example, understanding extreme areal rainfall is crucial in flood protection.
Davison, A. C. +2 more
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Semivariogram methods for modeling Whittle-Mat\'ern priors in Bayesian inverse problems
, 2020 We present a new technique, based on semivariogram methodology, for obtaining point estimates for use in prior modeling for solving Bayesian inverse problems.
Bardsley, Johnathan M. +2 more
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E-Jurnal Matematika, 2015 Spatial data is data that is presented in the geographic of an object, related to the location, shape and relationship of the earth in space. One of example of spatial data is rainfall. To determine the value of rainfall in an area, built to predict rain
PUTU MIRAH PURNAMA D. +2 more
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Inference for variograms [PDF]
, 2013 The empirical variogram is a standard tool in the investigation and modelling of spatial covariance. However, its properties can be difficult to identify and exploit in the context of exploring the characteristics of individual datasets.
Adrian W. Bowman +35 more
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Mathematics, 2020 Geostatistical interpolation methods, sometimes referred to as kriging, have been proven effective and efficient for the estimation of target quantity at ungauged sites.
Sompop Moonchai, Nawinda Chutsagulprom
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