Calculating the number of people with Alzheimer's disease in any country using saturated mutation models of brain cell loss that also predict widespread natural immunity to the disease.
Calculus of the estimators of linear quantile regression by the method ACCPM.
Capacity expansion of a deteriorating facility under uncertainty
Censored regression models with double exponential error distributions: an iterattive estimation procedure based on medians for correcting bias.
In this paper, we consider a simple iterative estimation procedure for censored regression models with symmetrical exponential error distributions. Although each step requires to impute the censored data with conditional medians, its tractability is guaranteed as well as its convergence at geometrical rate. Finally, as the final estimate coincides with a Huber M-estimator, its consistency and asymptotic normality are easily proved.
Chance constrained optimal beam design: Convex reformulation and probabilistic robust design
In this paper, we are concerned with a civil engineering application of optimization, namely the optimal design of a loaded beam. The developed optimization model includes ODE-type constraints and chance constraints. We use the finite element method (FEM) for the approximation of the ODE constraints. We derive a convex reformulation that transforms the problem into a linear one and find its analytic solution. Afterwards, we impose chance constraints on the stress and the deflection of the beam....
Change-point estimation from indirect observations. 2. Adaptation
We focus on the problem of adaptive estimation of signal singularities from indirect and noisy observations. A typical example of such a singularity is a discontinuity (change-point) of the signal or of its derivative. We develop a change-point estimator which adapts to the unknown smoothness of a nuisance deterministic component and to an unknown jump amplitude. We show that the proposed estimator attains optimal adaptive rates of convergence. A simulation study demonstrates reasonable practical...
Checking proportional rates in the two-sample transformation model
Transformation models for two samples of censored data are considered. Main examples are the proportional hazards and proportional odds model. The key assumption of these models is that the ratio of transformation rates (e. g., hazard rates or odds rates) is constant in time. A~method of verification of this proportionality assumption is developed. The proposed procedure is based on the idea of Neyman's smooth test and its data-driven version. The method is suitable for detecting monotonic as well...
Choosing the best -divergence goodness-of-fit statistic in multinomial sampling with linear constraints
In this paper we present a simulation study to analyze the behavior of the -divergence test statistics in the problem of goodness-of-fit for loglinear models with linear constraints and multinomial sampling. We pay special attention to the Rényi’s and -divergence measures.
Classical and variational differentiability of BSDEs with quadratic growth.
Coarse-graining schemes and a posteriori error estimates for stochastic lattice systems
The primary objective of this work is to develop coarse-graining schemes for stochastic many-body microscopic models and quantify their effectiveness in terms of a priori and a posteriori error analysis. In this paper we focus on stochastic lattice systems of interacting particles at equilibrium. The proposed algorithms are derived from an initial coarse-grained approximation that is directly computable by Monte Carlo simulations, and the corresponding numerical error is calculated using the...
Co-inertie de deux variables aléatoires hilbertiennes et approximation B-spline application en foresterie
Colinéarité et instabilité numérique dans le modèle linéaire
Colinearité et Instabilité Numérique dans le Modèle Linéaire
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
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
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...
Comparaison des méthodes de simulation d'un bruit blanc gaussien
Comparing estimation methods for the FPLD.
Comparison at optimal levels of classical tail index estimators: a challenge for reduced-bias estimation?
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....
Comparison between explicit and approximate degradation data analysis for linear paths.
Comparison of MINQUE and LMVQUIE by simulation