scholarly journals Hybrid Inversion Method to Estimate Hydraulic Transmissivity by Combining Multiple-Point Statistics and a Direct Inversion Method

2018 ◽  
Vol 50 (2) ◽  
pp. 147-167 ◽  
Author(s):  
Alessandro Comunian ◽  
Mauro Giudici
Keyword(s):  
Inversion Method ◽  
Multiple Point ◽  
Multiple Point Statistics ◽  
Direct Inversion

APPLICATIONS OF TWO NON-CENTRAL HYPERGEOMETRIC DISTRIBUTIONS OF BIASED SAMPLING STATISTICAL MODELS

2021 ◽  
Vol 4 (4) ◽  
pp. 415-424
Author(s):  
A. A. Issa ◽  
K. O. Adetunji ◽  
T. Alanamu ◽  
E. J. Adefila ◽  
K. A. Muhammed
Keyword(s):  
Statistical Models ◽  
Research Work ◽  
Hypergeometric Distribution ◽  
Biased Sampling ◽  
Inversion Method ◽  
Urn Model ◽  
Fisher Distribution ◽  
Direct Inversion ◽  
Mean And Variance ◽  
Hypergeometric Distributions

Statistical models of biased sampling of two non-central hypergeometric distributions Wallenius' and Fisher's distribution has been extensively used in the literature, however, not many of the logic of hypergeometric distribution have been investigated by different techniques. This research work examined the procedure of the two non-central hypergeometric distributions and investigates the statistical properties which includes the mean and variance that were obtained. The parameters of the distribution were estimated using the direct inversion method of hyper simulation of biased urn model in the environment of R statistical software, with varying odd ratios (w) and group sizes (mi). It was discovered that the two non - central hypergeometric are approximately equal in mean, variance and coefficient of variation and differ as odds ratios (w) becomes higher and differ from the central hypergeometric distribution with ω = 1. Furthermore, in univariate situation we observed that Fisher distribution at (ω = 0.2, 0.5, 0.7, 0.9) is more consistent than Wallenius distribution, although central hypergeometric is more consistent than any of them. Also, in multinomial situation, it was observed that Fisher distribution is more consistent at (ω = 0.2, 0.5), Wallenius distribution at (ω = 0.7, 0.9) and central hypergeometric at (ω = 0.2)    

Solving Speed and Memory Issues in Multiple-Point Statistics Simulation Program SNESIM

2013 ◽  
Vol 46 (2) ◽  
pp. 171-186 ◽  
Author(s):  
Sebastien Strebelle ◽  
Claude Cavelius
Keyword(s):  
Simulation Program ◽  
Multiple Point ◽  
Multiple Point Statistics
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