64,981 research outputs found
On the mean value of some new sequences
The main purpose of this paper is using the elementary and analytic methods
to study the mean value properties of the Smarandache repetitional sequence, and give two asymptotic formulas for it
Zero bias transformation and asymptotic expansions II : the Poisson case
We apply a discrete version of the methodology in \cite{gauss} to obtain a
recursive asymptotic expansion for \esp[h(W)] in terms of Poisson
expectations, where is a sum of independent integer-valued random variables
and is a polynomially growing function. We also discuss the remainder
estimations
Association Mining in Database Machine
Association rule is wildly used in most of the data mining technologies. Apriori algorithm is the fundamental association rule mining algorithm. FP-growth tree algorithm improves the performance by reduce the generation of the frequent item sets. Simplex algorithm is a advanced FP-growth algorithm by using bitmap structure with the simplex concept in geometry. The bitmap structure implementation is particular designed for storing the data in database machines to support parallel computing the association rule mining
Multiple defaults and contagion risks
We study multiple defaults where the global market information is modelled as
progressive enlargement of filtrations. We shall provide a general pricing
formula by establishing a relationship between the enlarged filtration and the
reference default-free filtration in the random measure framework. On each
default scenario, the formula can be interpreted as a Radon-Nikodym derivative
of random measures. The contagion risks are studied in the multi-defaults
setting where we consider the optimal investment problem in a contagion risk
model and show that the optimization can be effectuated in a recursive manner
with respect to the default-free filtration
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