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The approach developed by Kim and Steiner (2015) is situated within frequentist framework of statistics.
The mentioned methods above are in the framework of statistics theory, and they generally assume that the motion models of a maneuvering target are known.
In the preceding sections we describe the beta-binomial model within the frequentist framework of statistics.
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Within the multiple imputation perspective, we will describe approaches derived from the frequentist and Bayesian frameworks of statistics.
The results were analyzed within the framework of Weibull statistics.
The inference of the model parameters is performed in the framework of Bayesian statistics.
We propose an analytical solution to the on off problem within the framework of Bayesian statistics.
The basis to understand brittle fracture and stochastic failure of ceramics is discussed within the framework of Weibull statistics.
Multimodal image matching is discussed next in the framework of image statistics and partial differential equations (PDEs) with an eye on registering fMRI to the anatomy.
Using computational commutative algebra, especially Gröbner bases, we first find out several polynomial designs and then state existence results in R3 for spherical rotatable designs whose coordinates of their support points are known exactly, thus enabling us to derive the ideal of confounding polynomials thanks to tools defined in the framework of algebraic statistics.
As far as we know, these approaches have not been considered in the framework of order statistics from innid discrete random variables.
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