Search results for "Data analysis."
showing 10 items of 377 documents
Heavy-tailed targets and (ab)normal asymptotics in diffusive motion
2010
We investigate temporal behavior of probability density functions (pdfs) of paradigmatic jump-type and continuous processes that, under confining regimes, share common heavy-tailed asymptotic (target) pdfs. Namely, we have shown that under suitable confinement conditions, the ordinary Fokker-Planck equation may generate non-Gaussian heavy-tailed pdfs (like e.g. Cauchy or more general L\'evy stable distribution) in its long time asymptotics. For diffusion-type processes, our main focus is on their transient regimes and specifically the crossover features, when initially infinite number of the pdf moments drops down to a few or none at all. The time-dependence of the variance (if in existence…
Clusters of effects curves in quantile regression models
2018
In this paper, we propose a new method for finding similarity of effects based on quantile regression models. Clustering of effects curves (CEC) techniques are applied to quantile regression coefficients, which are one-to-one functions of the order of the quantile. We adopt the quantile regression coefficients modeling (QRCM) framework to describe the functional form of the coefficient functions by means of parametric models. The proposed method can be utilized to cluster the effect of covariates with a univariate response variable, or to cluster a multivariate outcome. We report simulation results, comparing our approach with the existing techniques. The idea of combining CEC with QRCM per…
Recent applications of point process methods in forestry statistics
2000
Forestry statistics is an important field of applied statistics with a long tradition. Many forestry problems can be solved by means of point processes or marked point processes. There, the "points" are tree locations and the "marks" are tree characteristics such as diameter at breast height or degree of damage by environmental factors. Point pro- cess characteristics are valuable tools for exploratory data analysis in forestry, for describing the variability of forest stands and for under- standing and quantifying ecological relationships. Models of point pro- cesses are also an important basis of modern single-tree modeling, that gives simulation tools for the investigation of forest stru…
EV-Scale Sterile Neutrino Search Using Eight Years of Atmospheric Muon Neutrino Data from the IceCube Neutrino Observatory
2020
Physical review letters 125(14), 141801 (1-11) (2020). doi:10.1103/PhysRevLett.125.141801
Spatio-temporal behaviour of the deep chlorophyll maximum in Mediterranean Sea: Development of a stochastic model for picophytoplankton dynamics
2013
In this paper, by using a stochastic reaction-diffusion-taxis model, we analyze the picophytoplankton dynamics in the basin of the Mediterranean Sea, characterized by poorly mixed waters. The model includes intraspecific competition of picophytoplankton for light and nutrients. The multiplicative noise sources present in the model account for random fluctuations of environmental variables. Phytoplankton distributions obtained from the model show a good agreement with experimental data sampled in two different sites of the Sicily Channel. The results could be extended to analyze data collected in different sites of the Mediterranean Sea and to devise predictive models for phytoplankton dynam…
Noise-enhanced propagation in a dissipative chain of triggers
2002
International audience; We study the influence of spatiotemporal noise on the propagation of square waves in an electrical dissipative chain of triggers. By numerical simulation, we show that noise plays an active role in improving signal transmission. Using the Signal to Noise Ratio at each cell, we estimate the propagation length. It appears that there is an optimum amount of noise that maximizes this length. This specific case of stochastic resonance shows that noise enhances propagation.
A strategic needs perspective on operations outsourcing and other inter-firm relationships
2013
Abstract This paper considers two issues: the formation of inter-firm relationships, and the choice of governance form. These have been widely investigated in both the strategic management and operations management fields. This paper contributes to the literature in three ways. First, we address why firms enter inter-firm relationships by hypothesizing that managers enter them to pursue three strategic needs, that is: efficiency/effectiveness, knowledge/learning, and global market access. Our first contribution evidences the relationship between the above strategic needs and a number of operational objectives that managers normally pursue in an inter-firm relationship. Second, we hypothesiz…
A software tool via web for the statistical data analysis; R-php
2007
The spread of Internet and the growing demand of services from the web users have changed and are still changing the way to organize the work or the study. Nowadays, the main part of information and many services are on the web and the software is going toward the same direction: in fact, the use of software implemented via web is ever-increasing, with a client-server logic that enables the “centralized” use of software installed on a server. In this paper we describe the Structure and the running of R-php, an environment for statistical analysis, freely accessible and attainable through the World Wide Web, based on the statistical environment R. R-php is based on two modules: a base module…
Symbolic Reductionist Model for Program Comprehension
2007
This article presents the main features of a novel construction, symbolic analysis, for automatic source code processing. The method is superior to the known methods, because it uses a semiotic, interpretative approach. Its most important processes and characteristics are considered here. We describe symbolic information retrieval and the process of analysis in which it can be used in order to obtain pragmatic information. This, in turn, is useful in understanding a current Java program version when developing a new version.
Fusing optical and SAR time series for LAI gap filling with multioutput Gaussian processes
2019
The availability of satellite optical information is often hampered by the natural presence of clouds, which can be problematic for many applications. Persistent clouds over agricultural fields can mask key stages of crop growth, leading to unreliable yield predictions. Synthetic Aperture Radar (SAR) provides all-weather imagery which can potentially overcome this limitation, but given its high and distinct sensitivity to different surface properties, the fusion of SAR and optical data still remains an open challenge. In this work, we propose the use of Multi-Output Gaussian Process (MOGP) regression, a machine learning technique that learns automatically the statistical relationships among…