Results 11 to 20 of about 4,118 (206)
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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Fast semivariogram computation using FPGA architectures [PDF]
SPIE Proceedings, 2015 The semivariogram is a statistical measure of the spatial distribution of data and is based on Markov Random Fields (MRFs). Semivariogram analysis is a computationally intensive algorithm that has typically seen applications in the geosciences and remote sensing areas.
Yamuna Lagadapati +2 more
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, 2011 Abstract. This study presents a weighted semivariogram model (WSVM) which is intended to reduce the uncertainties in the selection of the best-fit semivariogram model and associated parameters. The proposed WSVM is based on the combined forecast method, providing the weighted average semivariogram by summing up the product of estimated semivariograms ...
Wu, S.-J., Chen, P.-H., Yang, J.-C.
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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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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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Comparison of semivariogram models in rain gauge network design [PDF]
, 2018 The well-known geostatistics method (variance-reduction method) is common used to determine the optimal rain gauge network. The main problem in geostatistics method to determine the best semivariogram model in order to be used in estimating the variance.
Zalina, Mohd Daud +4 more
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Comparison Between Iterative Least Square and Nonparametric Epanechnikov Kernel in Semivariogram Modeling, Case study: Urban Land Cover in East Java Province [PDF]
ITM Web of ConferencesLandcover is an example of spatial data that contains location coordinate information along with the variables measured at each location, namely height, slope, and curvature.
Sari Kurnia Novita +3 more
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Semivariogram models for rice stem bug population densities estimated by ordinary kriging
Acta Scientiarum. Agronomy, 2020 Tibraca limbativentris is considered one of the main species of insect pests in irrigated rice. This species can be found in plants in the vegetative and reproductive stages.
Mauricio Paulo Batistella Pasini +3 more
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Comparison of semivariogram models in rain gauge network design [PDF]
, 2019 The well-known geostatistics method (variance-reduction method) is com- monly used to determine the optimal rain gauge network. The main problem in geostatis- tics method to determine the best semivariogram model in order to be used in estimating the ...
Mohd. Daud, Zalina +4 more
core +1 more source
Semivariogram models for estimating fig fly population density throughout the year
Pesquisa Agropecuária Brasileira, 2014 The objective of this work was to select semivariogram models to estimate the population density of fig fly (Zaprionus indianus; Diptera: Drosophilidae) throughout the year, using ordinary kriging.
Mauricio Paulo Batistella Pasini +2 more
doaj +1 more source