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Colinearité et Instabilité Numérique dans le Modèle Linéaire

Thierry Foucart (2010)

RAIRO - Operations Research

In this paper we give the expression of the multiple correlation coefficient in a linear model according to the coefficients of correlation. This expression makes it possible to analyze from a numerical point of view the instability of estimates in the case of collinear explanatory variables in the linear model or in the autoregressive model. This numerical approach, that we show on two examples, thus supplements the usual approach of the quasi colinearity, founded on the statistical properties...

Combining forecasts using the least trimmed squares

Jan Ámos Víšek (2001)

Kybernetika

Employing recently derived asymptotic representation of the least trimmed squares estimator, the combinations of the forecasts with constraints are studied. Under assumption of unbiasedness of individual forecasts it is shown that the combination without intercept and with constraint imposed on the estimate of regression coefficients that they sum to one, is better than others. A numerical example is included to support theoretical conclusions.

Combining System Dynamic Modeling and the Datar–Mathews Method for Analyzing Metal Mine Investments

Jyrki Savolainen, Mikael Collan, Pasi Luukka (2016)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

This paper presents how a dynamic system model can be used together with the Datar–Mathews real option analysis method for investment analysis of metal mining projects. The focus of the paper is on analyzing a project from the point of view of the project owner. The paper extends the Datar–Mathews real option analysis method by combining it with a dynamic system model. The model employs a dynamic discount rate that changes as the debt-level of the project changes. A numerical case illustration of...

Comparison at optimal levels of classical tail index estimators: a challenge for reduced-bias estimation?

M. Ivette Gomes, Lígia Henriques-Rodrigues (2010)

Discussiones Mathematicae Probability and Statistics

In this article, we begin with an asymptotic comparison at optimal levels of the so-called "maximum likelihood" (ML) extreme value index estimator, based on the excesses over a high random threshold, denoted PORT-ML, with PORT standing for peaks over random thresholds, with a similar ML estimator, denoted PORT-MP, with MP standing for modified-Pareto. The PORT-MP estimator is based on the same excesses, but with a trial of accommodation of bias on the Generalized Pareto model underlying those excesses....

Compartmental Models of Migratory Dynamics

J. Knisley, T. Schmickl, I. Karsai (2011)

Mathematical Modelling of Natural Phenomena

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

Francesco M. Malvestuto (2016)

Kybernetika

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...

Computational approaches to the design of low-energy buildings

Jarošová, Petra (2015)

Programs and Algorithms of Numerical Mathematics

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

Maria Manuela Neves, Clara Cordeiro (2011)

Discussiones Mathematicae Probability and Statistics

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

Aleksander Janicki (1995)

Applicationes Mathematicae

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

Aleksander Weron (1995)

Applicationes Mathematicae

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

Viktor Witkovský (2001)

Kybernetika

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 p -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...

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