Comparison of two common estimators of the ratio of the means of independent normal variables in agricultural research.
Compartmental Models of Migratory Dynamics
Compartmentalization is a general principle in biological systems which is observable on all size scales, ranging from organelles inside of cells, cells in histology, and up to the level of groups, herds, swarms, meta-populations, and populations. Compartmental models are often used to model such phenomena, but such models can be both highly nonlinear and difficult to work with.Fortunately, there are many significant biological systems that are amenable to linear compartmental models which are often...
Compositional models, Bayesian models and recursive factorization models
Compositional models are used to construct probability distributions from lower-order probability distributions. On the other hand, Bayesian models are used to represent probability distributions that factorize according to acyclic digraphs. We introduce a class of models, called recursive factorization models, to represent probability distributions that recursively factorize according to sequences of sets of variables, and prove that they have the same representation power as both compositional...
Compound Nonlinear Congruential Pseudorandom Numbers.
Computation of Greeks for barrier and look-back options using Malliavin calculus.
Computation of Greeks using Malliavin's calculus in jump type market models.
Computational approaches to the design of low-energy buildings
European and Czech directives and technical standards, approved in several last years, force substantial changes in thermal behaviour of all buildings, including new and reconstructed one- or more-family houses, block of fl ats, etc., especially radical decrease of their energy requirements. This stimulates the development of advanced materials, structures and technologies. Since no reliable experience with their design is available, robust and non-expensive computational simulation approaches,...
Computational intensive methods for prediction and imputation in time series analysis
One of the main goals in times series analysis is to forecast future values. Many forecasting methods have been developed and the most successful are based on the concept of exponential smoothing, based on the principle of obtaining forecasts as weighted combinations of past observations. Classical procedures to obtain forecast intervals assume a known distribution for the error process, what is not true in many situations. A bootstrap methodology can be used to compute distribution free forecast...
Computer simulation of a nonlinear model for electrical circuits with α-stable noise
The aim of this paper is to apply the appropriate numerical, statistical and computer techniques to the construction of approximate solutions to nonlinear 2nd order stochastic differential equations modeling some engineering systems subject to large random external disturbances. This provides us with quantitative results on their asymptotic behavior.
Computer-aided modeling and simulation of electrical circuits with α-stable noise
The aim of this paper is to demonstrate how the appropriate numerical, statistical and computer techniques can be successfully applied to the construction of approximate solutions of stochastic differential equations modeling some engineering systems subject to large disturbances. In particular, the evolution in time of densities of stochastic processes solving such problems is discussed.
Computing the distribution of a linear combination of inverted gamma variables
A formula for evaluation of the distribution of a linear combination of independent inverted gamma random variables by one-dimensional numerical integration is presented. The formula is direct application of the inversion formula given by Gil–Pelaez [gil-pelaez]. This method is applied to computation of the generalized -values used for exact significance testing and interval estimation of the parameter of interest in the Behrens–Fisher problem and for variance components in balanced mixed linear...
Computing the minimal efficiency of designs by a differentiable approximation of -optimality criteria.
Computing the reliability of systems with statistical dependent elements.
Concomitants and linear estimators in an i-dimensional extremal model.
We consider here a multivariate sample Xj = (X1.j > ... > Xi.j), 1 ≤ j ≤ n, where the Xj, 1 ≤ j ≤ n, are independent i-dimensional extremal vectors with suitable unknown location and scale parameters λ and δ respectively. Being interested in linear estimation of these parameters, we consider the multivariate sample Zj, 1 ≤ j ≤ n, of the order statistic of largest values and their concomitants, and the best linear unbiased estimators of λ and δ based on such multivariate sample. Computational...
Conditional problem for objective probability
Marginal problem (see [Kel]) consists in finding a joint distribution whose marginals are equal to the given less-dimensional distributions. Let’s generalize the problem so that there are given not only less-dimensional distributions but also conditional probabilities. It is necessary to distinguish between objective (Kolmogorov) probability and subjective (de Finetti) approach ([Col,Sco]). In the latter, the coherence problem incorporates both probabilities and conditional probabilities in a unified...
Confidence intervals for reliability functions of an exponential distribution under random censorship
Continuous -methods for the stochastic pantograph equation.
Contribuciones a la generalización del problema de compensación por grupos de Helmert-Pranis Pranievich.
The paper presents in a generalized form the problem of the geodetic network adjustment by the Helmert-Pranis Pranievich groups method (groups with junction points included or not). The adjustment problem, as well as the cofactor matrix derivation for the partial-independent and linkage unknowns, was completely formulated by transformed weight matrix definition and usage. A complete sequence of the computing stages for the geodetic networks divided into groups without junction points was given for...
Control of uncertain processes: applied theory and algorithms
Convergence issues in the theory and practice of iterative aggregation/disaggregation methods.