Random Dot Product Graph Models for Social Networks
... existence of directed cycles, among others. Thus there is considerable interest in new models for complex networks that exhibit a power-law like degree sequence, small diameter, and clustering, and are different enough from the three main model classes to exhibit other properties of complex network ...
... existence of directed cycles, among others. Thus there is considerable interest in new models for complex networks that exhibit a power-law like degree sequence, small diameter, and clustering, and are different enough from the three main model classes to exhibit other properties of complex network ...
Understanding the concept of outlier and its relevance to the
... So, behind of every precise definition should directly or indirectly be the correct understanding of the sample. Secondly, nevertheless, the mathematical definition is so simple, in real life cases, it is not so simple, even sometimes difficult to consider whether the data in question is sample or n ...
... So, behind of every precise definition should directly or indirectly be the correct understanding of the sample. Secondly, nevertheless, the mathematical definition is so simple, in real life cases, it is not so simple, even sometimes difficult to consider whether the data in question is sample or n ...
Probing the QGP with Quarkonium
... J/ψs are not at rest in the QGP! what is the potential for moving heavy quarks ? The screening effect is due to the rearrangement of the charged particles when a pair of heavy quarks (source) is put into the medium. When the source moves in the medium, it costs some time for the screening charges to ...
... J/ψs are not at rest in the QGP! what is the potential for moving heavy quarks ? The screening effect is due to the rearrangement of the charged particles when a pair of heavy quarks (source) is put into the medium. When the source moves in the medium, it costs some time for the screening charges to ...
The question:Let N points be scattered at random on the surface of
... analog of the convex hull, we will call this the spherical hull of {p_k}. Now consider the sphere, S^{n-2}, as the equator of S^{n-1}. We can generate uniformly distributed points on the equator by generating uniformly distributed points on the sphere and mapping them to the equator using the map P: ...
... analog of the convex hull, we will call this the spherical hull of {p_k}. Now consider the sphere, S^{n-2}, as the equator of S^{n-1}. We can generate uniformly distributed points on the equator by generating uniformly distributed points on the sphere and mapping them to the equator using the map P: ...
here
... x | g(C, x), g(D, x). It remains to distribute the remaining term (x + 1)2 (x2 + 1)2 (x4 + 1)2 ; we can view each of these 6 factors as being “assigned” to either C or D. Note that since g(C, 1) = g(D, 1) = 8, and each of the factors x + 1, x2 + 1, x4 + 1 evaluates to 2 when x = 1, exactly three fac ...
... x | g(C, x), g(D, x). It remains to distribute the remaining term (x + 1)2 (x2 + 1)2 (x4 + 1)2 ; we can view each of these 6 factors as being “assigned” to either C or D. Note that since g(C, 1) = g(D, 1) = 8, and each of the factors x + 1, x2 + 1, x4 + 1 evaluates to 2 when x = 1, exactly three fac ...
Same-Decision Probability: A Confidence Measure for
... made based on a diagnostician’s beliefs about the health state of the system, and the extent to which they are certain or uncertain about it. In this section, we highlight an example of a threshold-based decision made under a simple but generally applicable context, where observations are given by n ...
... made based on a diagnostician’s beliefs about the health state of the system, and the extent to which they are certain or uncertain about it. In this section, we highlight an example of a threshold-based decision made under a simple but generally applicable context, where observations are given by n ...
Combinatorial Description and Free Convolution
... 2.4. From moments to cumulants. “Freeness” of random variables is defined in terms of mixed moments; namely the defining property is that very special moments (alternating and centered ones) have to vanish. This requirement is not easy to handle in concrete calculations. Thus we will present here an ...
... 2.4. From moments to cumulants. “Freeness” of random variables is defined in terms of mixed moments; namely the defining property is that very special moments (alternating and centered ones) have to vanish. This requirement is not easy to handle in concrete calculations. Thus we will present here an ...
the bayesian revolution in genetics
... obtained simply as the product of the prior P(Φ) and the likelihood P(D|Φ). Typically, the likelihood will arise from a statistical model in which it is necessary to consider how the data can be ‘explained’ by the parameter(s). The prior is an assumed distribution of the parameter that is obtained f ...
... obtained simply as the product of the prior P(Φ) and the likelihood P(D|Φ). Typically, the likelihood will arise from a statistical model in which it is necessary to consider how the data can be ‘explained’ by the parameter(s). The prior is an assumed distribution of the parameter that is obtained f ...
Events That Are Not Mutually Exclusive
... Since some of Namiko’s paintings are both watercolors and landscapes, these events are not mutually exclusive. Use the rule for two events that are not mutually exclusive. The total number of paintings from which to choose is 30. ...
... Since some of Namiko’s paintings are both watercolors and landscapes, these events are not mutually exclusive. Use the rule for two events that are not mutually exclusive. The total number of paintings from which to choose is 30. ...
One-Counter Markov Decision Processes
... Motivation for studying OC-MDPs comes from several different directions. Firstly, it is very natural, both in queueing theory and in other contexts, to consider an “adversarial” extension of stochastic models like QBDs, so that stochastic assumptions can sometimes be replaced by “worst-case” or “bes ...
... Motivation for studying OC-MDPs comes from several different directions. Firstly, it is very natural, both in queueing theory and in other contexts, to consider an “adversarial” extension of stochastic models like QBDs, so that stochastic assumptions can sometimes be replaced by “worst-case” or “bes ...
Probability box
),steps=500.png?width=300)
A probability box (or p-box) is a characterization of an uncertain number consisting of both aleatoric and epistemic uncertainties that is often used in risk analysis or quantitative uncertainty modeling where numerical calculations must be performed. Probability bounds analysis is used to make arithmetic and logical calculations with p-boxes.An example p-box is shown in the figure at right for an uncertain number x consisting of a left (upper) bound and a right (lower) bound on the probability distribution for x. The bounds are coincident for values of x below 0 and above 24. The bounds may have almost any shapes, including step functions, so long as they are monotonically increasing and do not cross each other. A p-box is used to express simultaneously incertitude (epistemic uncertainty), which is represented by the breadth between the left and right edges of the p-box, and variability (aleatory uncertainty), which is represented by the overall slant of the p-box.