[PDF] Top 20 Singularity analysis for heavy tailed random variables
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Singularity analysis for heavy tailed random variables
... The analytic proof of the theorems is complemented by clear probabilistic heuris- tics. Our results cover different regimes: a small steps or moderate deviations regime, where a classical variant of a local central limit ... See full document
41
Asymptotic tail probability of weighted infinite sum of conditionally dependent and consistently varying tailed random variables
... This paper will mainly focus on the asymptotic behavior of the tail probability of a weighted infinite sum of heavy-tailed r.v.s under the above two extended conditional de- pendence structures. In the rest ... See full document
15
Heavy-tailed distribution in the presence of dependence in insurance and finance
... i.i.d. random pairs and that each pair obeys a dependence structure described via the conditional tail probability of a claim size given the interarrival time before the ...are heavy-tail distribution ... See full document
82
Heavy-tailed distributions : data, diagnostics, and new developments
... distributed random variables with tail index 1 < α < ...these random variables is infinite, as is the variance of any finite sum of these ...n variables is also infinite, for any ... See full document
65
Extended power law scaling of heavy tailed random air permeability fields in fractured and sedimentary rocks
... 21 m across and 6 m high, includes a lower bioturbated facies and an upper cross-bedded facies (Fig. 8). A total of 515 per- meability measurements were taken in triplicate at a sample spacing of 15 cm along three ... See full document
12
Heavy-tailed modeling of CROBEX
... of random variables R s and R t+s , while the term in the denominator represents the product of the empirical standard deviations of random variables R s and R t+s , 0 ≤ s < s + t ≤ ... See full document
20
Random permutations with logarithmic cycle weight
... Poisson variables and also compute the total varia- tion distance between both ...to random permutations under this ...complex analysis and ...of singularity analysis to generating ... See full document
29
Impact of Different Random Initializations on Generalization Performance of Extreme Learning Machine
... with random numbers obeying 24 different continuous probability distributions, we compare the training and testing accuracies of 24 ELMs on 30 UCI data ...statistical analysis reflect that (1) the ... See full document
18
Heavy-tailed Phenomena and Tail Index Inference
... as heavy-tailed distributed, or following a power-law ...the random variables under investigation follow a normal distribution is highly ... See full document
132
A review of conditional rare event simulation for tail probabilities of heavy tailed random variables
... The first logarithmic efficient algorithm was proposed in [5] for the regularly varying case. This is a Conditional Monte Carlo estimator and based on order statistics. The reference [22] proposes a variant of the latter ... See full document
22
Generalized independent low rank matrix analysis using heavy tailed distributions for blind source separation
... more heavy-tailed ...a random variable, namely, a linear combination of two independent random variables generated from the same distribution family also has the same distribution up to ... See full document
25
Concentration inequalities for empirical processes of linear time series
... innovations. Heavy-tailed distributions have been substantially studied in the ...and heavy tails in the high frequency asset return ...independent heavy-tailed random ...and ... See full document
46
Non-homogeneous random walks with non-integrable increments and heavy-tailed random walks on strips
... non-homogeneous random walks with non-integrable increments, including transience, almost-sure bounds, and existence and non-existence of moments for first-passage and last-exit ...including random walks ... See full document
28
Some conclusions of the exchangeable random variables and the independent identical distribution random variables
... exchangeable random variables sequences, the Definetti’s theorem does not work to finite exchangeable random variables sequences, it is therefore necessary to find other techniques to solve ... See full document
6
Continuous random variables
... The waiting time, X hours, for the next customer to arrive in a shop is known to have a probability density function f (x) = αe −αx , x ≥ 0, and zero elsewhere, where α is a constant. a Use calculus to show that f (x ) ... See full document
30
A Family of Loss Distributions with an Application to the Vehicle Insurance Loss Data
... the lognormal and gamma distributions causing difficulties in the estimation process and computation of mathematical properties. Whereas, the Weibull model, which is a super-exponential distribution is a prominent ... See full document
14
Discrete random variables
... A random variable (denoted by X , Y , …) is a variable whose value is determined by the outcome of a random ...the random variable X could be defined as the number of 6s ... See full document
56
On Complex Random Variables
... multivariate random variable of Z is a complex multivariate normal variable of dimension n if all nondegenerate complex linear combination of Z have a complex univariate normal ... See full document
10
Manpower Systems Operating under Heavy and Light Tailed Inter Exit Time Distributions
... light tailed inter-exit time distribution B t ( ) giv- ing E(τ light ) and 2) for a specific heavy tailed distribution B t ( ) giving E(τ heavy ... See full document
7
Stochastic daily precipitation model with a heavy-tailed component
... It is well known that the above continuous distributions tend to underestimate the heavy precipitation. Furrer and Katz (2008) developed a flexible approach, based on gamma and GP distributions, in order to model ... See full document
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