Results 91 to 100 of about 19,957,777 (200)

Regression Extensions of the New Polynomial Exponential Distribution: NPED-GLM and Poisson–NPED Count Models with Applications in Engineering and Insurance

Computation
The New Polynomial Exponential Distribution (NPED), introduced by Beghriche et al. (2022), provides a flexible one-parameter family capable of representing diverse hazard shapes and heavy-tailed behavior. Regression frameworks based on the NPED, however,
Halim Zeghdoudi, Sandra S. Ferreira, Vinoth Raman, Dário Ferreira   +3 more
doaj   +1 more source

Lattice-Search Runtime Distributions May Be

, 2007
Recent empirical studies show that runtime distributions of backtrack procedures for solving hard combinatorial problems often have intriguing properties.
Ashwin Srinivasan, Heavy-Tailed Filip Zelezny   +1 more
core  

Testing for finite variance with applications to vibration signals from rotating machines

Journal of Mathematics in Industry
In this paper we propose an algorithm for testing whether the independent observations come from finite-variance distribution. The preliminary knowledge about the data properties may be crucial for its further analysis and selection of the appropriate ...
Katarzyna Skowronek, Radosław Zimroz, Agnieszka Wyłomańska   +2 more
doaj   +1 more source

Polar Depth for Potentially Heavy-Tailed Data

Motivated by the analysis of the behaviour of extremes from multivariate heavy-tailed distributions, we introduce a novel notion of statistical depth, referred to as Polar Depth. The polar depth function is naturally expressed in polar coordinates, as is the limiting distribution of a regularly varying random variable, beyond asymptotically large ...
Clemençon, Stephan, Fernándes, Carlos, Mozharovskyi, Pavlo, Sabourin, Anne   +3 more
openaire   +2 more sources

Extreme Value Analysis of Teletraffic Data [PDF]

An empirically verified characteristic of the expanding area of Internet is the longtailness of phenomena such as cpu time to complete a job, call holding times, files lengths requested, inter-arrival times and so on.
Panaretos, John, Tsourti, Zoi
core  

Learning Time-Varying Graphs for Heavy-Tailed Data Clustering

Time-varying graph models serve as powerful tools for capturing the dynamic structure of data defined over networks, where the interactions between entities vary with time.
Perez Palomar, Daniel, Javaheri, Seyed Amirhossein   +1 more
core   +1 more source

Gaussian Tests of "Extremal White Noise" for Dependent, Heterogeneous, Heavy Tailed Strochastic Processes with an Application [PDF]

We develop a non-parametric test of tail-specific extremal serial dependence for possibly heavy-tailed time series. The test statistic is asymptotically chi-squared under a null of "extremal white noise", as long as extremes of the time series are Near ...
Jonathan B. Hill
core  

Nonparametric Quantile Regression with Heavy-Tailed and Strongly Dependent Errors [PDF]

We consider nonparametric estimation of the conditional qth quantile for stationary time series. We deal with stationary time series with strong time dependence and heavy tails under the setting of random design.
Toshio Honda
core  

When Random Variation Results in Functional Segregation. [PDF]

Neuroinformatics
Barfield J, Kells P, Gautam S, Shew W.
europepmc   +1 more source

Fitting financial time series data to heavy tailed distribution

, 2002
Financial data, such as daily or monthly maximum log return of stock price usually possess heavy tail and skewness properties. In this thesis, we consider stock price data of computer hardware and money center banks.
Huang, Liu-Yuen
core