Search results for "stochastic"
showing 10 items of 1018 documents
Nucleotide's bilinear indices: Novel bio-macromolecular descriptors for bioinformatics studies of nucleic acids. I. Prediction of paromomycin's affin…
2009
A new set of nucleotide-based bio-macromolecular descriptors are presented. This novel approach to bio-macromolecular design from a linear algebra point of view is relevant to nucleic acids quantitative structure-activity relationship (QSAR) studies. These bio-macromolecular indices are based on the calculus of bilinear maps on Re(n)[b(mk)(x (m),y (m)):Re(n) x Re(n)--Re] in canonical basis. Nucleic acid's bilinear indices are calculated from kth power of non-stochastic and stochastic nucleotide's graph-theoretic electronic-contact matrices, M(m)(k) and (s)M(m)(k), respectively. That is to say, the kth non-stochastic and stochastic nucleic acid's bilinear indices are calculated using M(m)(k)…
Statistical Analysis of Biological Models with Uncertainty
2020
In this contribution relevant biological models, based on random differential equations, are studied. For the sake of generality, we assume that the initial condition and the biological model parameters are dependent random variables with arbitrary probability distributions. We present a general methodology that enables us to provide a full probabilistic description of the solution stochastic process for each stochastic model. The statistical analysis is performed through the calculation of the first probability function by applying the random variable transformation technique. From the first probability density function, we can calculate any one-dimensional moment of the solution, includin…
Identifying Portfolio-Based Risk Factors in Foreign Exchange Markets
2018
This paper shows that a link between the conditional mean and conditional volatility of any factor-mimicking portfolio in the foreign exchange (FX) market must exist if the proposed portfolio-based currency factor is priced and the pricing kernel has a linear factor structure. Thereby, this paper tests whether the carry risk factor and currency momentum are priced risk factors. Surprisingly, the carry risk factor does not meet the necessary conditions consistent with being a priced risk factor, whereas currency momentum indeed meets those criteria. The findings also indicate that the relation between the conditional mean and conditional risk is moreover economically reasonable for the curre…
Evolutionary dynamics of imatinib-treated leukemic cells by stochastic approach
2008
The evolutionary dynamics of a system of cancerous cells in a model of chronic myeloid leukemia (CML) is investigated by a statistical approach. Cancer progression is explored by applying a Monte Carlo method to simulate the stochastic behavior of cell reproduction and death in a population of blood cells which can experience genetic mutations. In CML front line therapy is represented by the tyrosine kinase inhibitor imatinib which strongly affects the reproduction of leukemic cells only. In this work, we analyze the effects of a targeted therapy on the evolutionary dynamics of normal, first-mutant and cancerous cell populations. Several scenarios of the evolutionary dynamics of imatinib-tr…
The Random Neural Network Model for the On-line Multicast Problem
2005
In this paper we propose the adoption of the Random Neural Network Model for the solution of the dynamic version of the Steiner Tree Problem in Networks (SPN). The Random Neural Network (RNN) is adopted as a heuristic capable of improving solutions achieved by previously proposed dynamic algorithms. We adapt the RNN model in order to map the network characteristics during a multicast transmission. The proposed methodology is validated by means of extensive experiments.
The analytic hierarchy process with stochastic judgements
2014
The analytic hierarchy process (AHP) is a widely-used method for multicriteria decision support based on the hierarchical decomposition of objectives, evaluation of preferences through pairwise comparisons, and a subsequent aggregation into global evaluations. The current paper integrates the AHP with stochastic multicriteria acceptability analysis (SMAA), an inverse-preference method, to allow the pairwise comparisons to be uncertain. A simulation experiment is used to assess how the consistency of judgements and the ability of the SMAA-AHP model to discern the best alternative deteriorates as uncertainty increases. Across a range of simulated problems results indicate that, according to c…
COMPARATIVE ASSESSMENT OF SEVERAL MULTI-CRITERIA DECISION ANALYSIS TOOLS FOR MANAGEMENT OF CONTAMINATED SEDIMENTS
2007
Over the past several decades, environmental decision-making strategies have evolved into increasingly more sophisticated, information-intensive, and complexapproaches including expert judgment, cost-benefit analysis, toxicological risk assessment, comparative risk assessment, and a number of methods forincorporating public and stakeholder values. This evolution has led to an improved array of decision-making aids, including the development of Multi-CriteriaDecision Analysis (MCDA) tools that offer a scientifically sound decision analytical framework. The existence of different MCDA methods and the availability of corresponding software contribute to the possibility of practical implementat…
SMAA in Robustness Analysis
2016
Stochastic multicriteria acceptability analysis (SMAA) is a simulation based method for discrete multicriteria decision aiding problems where information is uncertain, imprecise, or partially missing. In SMAA, different kind of uncertain information is represented by probability distributions. Because SMAA considers simultaneously the uncertainty in all parameters, it is particularly useful for robustness analysis. Depending on the problem setting, SMAA determines all possible rankings or classifications for the alternatives, and quantifies the possible results in terms of probabilities. This chapter describes SMAA in robustness analysis using a real-life decision problem as an example. Bas…
Efficient Computation of Multiscale Entropy over Short Biomedical Time Series Based on Linear State-Space Models
2017
The most common approach to assess the dynamical complexity of a time series across multiple temporal scales makes use of the multiscale entropy (MSE) and refined MSE (RMSE) measures. In spite of their popularity, MSE and RMSE lack an analytical framework allowing their calculation for known dynamic processes and cannot be reliably computed over short time series. To overcome these limitations, we propose a method to assess RMSE for autoregressive (AR) stochastic processes. The method makes use of linear state-space (SS) models to provide the multiscale parametric representation of an AR process observed at different time scales and exploits the SS parameters to quantify analytically the co…