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Estimation using spatially distributed multivariate data: An example with coal quality

https://doi.org/10.1007/bf01036071
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-94-010-1470-0_22openalex-snapshot
Improving the Uranium Deposits Estimations (The Novazza Case)
inferredcites →https://doi.org/10.1007/978-94-010-1470-0_24openalex-snapshot
A Case Study: Multivariate Properties of Bentonite in Northeastern Wyoming
inferredcites →https://doi.org/10.1007/bf01032887openalex-snapshot
Matrix formulation of co-kriging
inferredcites →https://doi.org/10.1007/bf01036070openalex-snapshot
The multigaussian approach and its applications to the estimation of local reserves
inferredcites →https://doi.org/10.2307/2286247openalex-snapshot
Advanced Geostatistics in the Mining Industry.

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Enhancing Multivariate Geostatistical Simulation in Mine Tailings Using the Projection Pursuit Multivariate Transform and Coregionalization Analysis
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inferred← citeshttps://doi.org/10.1016/j.coal.2006.08.008openalex-snapshot
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Multivariate geostatistical simulation of coal quality data by independent components
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Fault and non-fault areas detection based on seismic data through min/max autocorrelation factors and fuzzy classification
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Hierarchical Bayesian Nearest Neighbor Co-Kriging Gaussian Process Models; An Application to Intersatellite Calibration
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