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Generalized weighted random convergence in probability

Applied Mathematics and Computation, 2014
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Tail Inference With Probability Weighted Moments

Mathematical Methods in the Applied Sciences
ABSTRACTThe tail of a probability distribution captures important information about the magnitude and frequency of extreme events. Thus, understanding the tail behavior is crucial in decision making and risk assessment. Statistical analysis and predictions of extreme events often require the estimation of the extreme value index, a key parameter that ...
Frederico Caeiro   +2 more
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Emotional balance and probability weighting

Theory and Decision, 2012
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Charupat, Narat   +4 more
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Tensor products and probability weights

International Journal of Theoretical Physics, 1987
We study a general tensor product for two collections of related physical operations or observations. This is a free product, subject only to the condition that the operations in the first collection fail to have any influence on the statistics of operations in the second collection and vice versa.
Kläy, M., Randall, C., Foulis, D.
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Weighted Probability Density Estimator with Updated Bandwidths

Journal of Systems Science and Complexity
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Yi Wu   +3 more
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Probability inequalities for weighted distributions

Journal of Statistical Planning and Inference, 2012
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Li, Ying, Yu, Li, Hu, Taizhong
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Additive weights under the Balanced Probability Model

Computing, 1995
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Probability Weighting of Spatial Filters*

Journal of the Optical Society of America, 1971
The optimum spatial filter for the detection of randomly located patterns is discussed. When the signal-to-noise (S/N) ratio is low, the optimum filter is described by the product of the Fourier transform of the probability distribution describing the signal location and the conjugate of the signal spatial spectrum divided by the noise spectral density.
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Probability Weighting and Asset Prices

SSRN Electronic Journal, 2012
In the present paper, we estimate a monthly index of aggregate skewness preference. This index is derived from the representative agent's nonparametric probability weighting function. Consistent with findings from lab experiments, probability weighting functions depend on sentiment and their average is inverse-S shaped.
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Quantum probability weighted paths

Acta Physica Academiae Scientiarum Hungaricae, 1969
The paper is concerned with the generalization ofFeynman’s method. A real “probability” measure is introduced for weighting trajectories and this is expressed as the boundary case of a measure containing one real parameter. For the finite values of the real parameter an equation of motion of the Fokker-Planck type is used.
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