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The multiple inverse sampling may be viewed as an improved version of quota sampling in some sense.
We then modify the multiple inverse sampling design to a version with taking a simple random sample at the beginning similar to Chang et al (J. Statist. Plan. Inference 69 (1998) 209) and a truncated version similar to Chang et al (J. Statist. Plan. Inference 76 (1999) 215).
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We extend traditional inverse sampling to multiple case.
Fig. 4. Results of stress tensor inversion by the multiple inverse method.
The multiple inverse method of stress tensor inversion detected two normal-faulting stress states that dominate in different regions.
The multiple inverse method (MIM) of stress inversion resolves statistically significant stress heterogeneities in the study area.
multiple inverse method.
A randomized version of the inverse sampling is introduced.
All individuals are weighted by their inverse sampling probability.
Each point in the lower hemisphere represents a solution for each subset calculated by the multiple inverse method.
Data was weighted with inverse sampling probabilities.
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