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A design-based framework for optimal stratification using super-population models with application on real data set of breast cancer. [PDF]
PLoS OneDanish F.
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A novel Hellinger distance-based regret theory method for spherical fuzzy decision making model and its application in logistics. [PDF]
Sci RepRen H, Zhou H.
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Discrete Poisson Haq distribution with mathematical properties and count data modeling. [PDF]
Sci RepAlomair AM +3 more
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From burnout to balance: the role of peer-assisted learning in college life. [PDF]
BMC Med EducJimenez N +4 more
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Enhanced slope stability prediction using ensemble machine learning techniques. [PDF]
Sci RepYadav DK +4 more
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Neutrosophic Perspective of Neutrosophic Probability Distributions and its Application
International Journal of Neutrosophic Science, 2021Neutrosophical probability is concerned with inequitable and defective topics and processes. This is a subset of Neutrosophic measures that includes a prediction of an event (as opposed to indeterminacy) as well as a prediction of some unpredictability.
M. Lathamaheswari +3 more
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Annals of the University of Craiova Mathematics and Computer Science Series, 2023
In this paper, we define the notions of neutrosophic $ \mathfrak{Y} $-Ces\`aro summability of a sequence of order $ \alpha $, neutrosophic $ \mathfrak{Y} $-lacunary statistical convergence of order $ \alpha $, neutrosophic strongly $ \mathfrak{Y} $-lacunary statistical convergence of order $ \alpha $ and neutrosophic strongly $ \mathfrak{Y} $-Ces\`aro
Granados Carlos +2 more
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In this paper, we define the notions of neutrosophic $ \mathfrak{Y} $-Ces\`aro summability of a sequence of order $ \alpha $, neutrosophic $ \mathfrak{Y} $-lacunary statistical convergence of order $ \alpha $, neutrosophic strongly $ \mathfrak{Y} $-lacunary statistical convergence of order $ \alpha $ and neutrosophic strongly $ \mathfrak{Y} $-Ces\`aro
Granados Carlos +2 more
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2021
The importance of normal probability distribution can’t be denied in inferential statistics due to its wide applicability. In classical statistics, the parameters of the normal probability distribution are assumed to be certain and complete, but in real-life problems, these can be imprecise, vague, unclear, or indeterminate.
Rehan Ahmad Khan Sherwani +5 more
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The importance of normal probability distribution can’t be denied in inferential statistics due to its wide applicability. In classical statistics, the parameters of the normal probability distribution are assumed to be certain and complete, but in real-life problems, these can be imprecise, vague, unclear, or indeterminate.
Rehan Ahmad Khan Sherwani +5 more
openaire +1 more source