Bootstrapped Spatial Statistics: A More Robust Approach to the Analysis of Finite Strain Data
IR@C-MMACS: CSIR-Centre for Mathematical Modelling and Computer Simulation, Bangalore
View Archive Info| Field | Value | |
| Title |
Bootstrapped Spatial Statistics:
A More Robust Approach to the Analysis of Finite Strain Data
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| Creator |
Mukul, Malay
V, Anil Kumar |
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| Subject |
Finite Element Analysis
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| Description |
Standard spatial statistics involves exploratory data analysis (EDA) and the computation of a
semi-variogram from spatial data such as the finite strain data from a thrust sheet. However,
the uncertainties in the computation of the most of the EDA and the semi-variogram
parameters cannot be estimated; standard EDA allows the computation of the uncertainties
associated with only the sample mean. Bootstrapped EDA is found to be more robust than the
standard EDA because it allows uncertainties to be computed for all EDA parameters.
Bootstrapped spatial statistics also allows the computation of a better and a more robust semivariogram
than standard spatial statistics as the uncertainties associated with the semivariogram
parameters can be ascertained. The range (a)= 750 m and sill (c) = 0.008 values
associated with the exponential semi-variogram computed by Mukul (Journal of Structural
Geology, 20 (4), 371-384, 1998) for the finite strain data from the Sevier fold-and-thrust belt
in western USA, was recomputed using Bootstrapped Spatial Statistics. The range (a) was
recomputed as 719.4 ±32.2048 and the sill (c) as 0.0097± 0.0004. Kriging estimates obtained
using the Bootstrapped semi-variogram indicate that the results are practically insensitive to
the uncertainty associated with the estimation of parameters of the semi-variogram used.
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| Publisher |
CSIR Centre for Mathematical Modelling and Computer Simulation
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| Date |
2002-01
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| Type |
Monograph
NonPeerReviewed |
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| Format |
application/pdf
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| Identifier |
http://cir.cmmacs.ernet.in/220/1/pd0201d.pdf
Mukul, Malay and V, Anil Kumar (2002) Bootstrapped Spatial Statistics: A More Robust Approach to the Analysis of Finite Strain Data. Project Report. CSIR Centre for Mathematical Modelling and Computer Simulation , C-MMACS,Bangalore 560037,India. (Unpublished) |
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| Relation |
http://cir.cmmacs.ernet.in/220/
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