Packing graphs: The packing problem solved.
Pairs of successes in Bernoulli trials and a new n-estimator for the binomial distribution
The problem of estimating the number, n, of trials, given a sequence of k independent success counts obtained by replicating the n-trial experiment is reconsidered in this paper. In contrast to existing methods it is assumed here that more information than usual is available: not only the numbers of successes are given but also the number of pairs of consecutive successes. This assumption is realistic in a class of problems of spatial statistics. There typically k = 1, in which case the classical...
Paradigme logique des écritures relationnelles de quelques critères fondamentaux d'association
Parallel genetic algorithms with migration for the hybrid flow shop scheduling problem.
Parallelization algorithms for modeling ARM processes.
Parameter Estimation for a Bivariate Lifetime Distribution in Reliability with Multivariate Extensions.
Parameter estimation for uniform autoregressive processes.
Parameter estimation for uniform maximum process.
Parameter estimation in cosine regression
Parameter Estimation in Linear Regression Models With Stationary Arma(p,q)-Errors Using Automatic Differentiation
Parameter estimation in stochastic systems: some recent results and applications
Parameter estimation of S-distributions with alternating regression.
We propose a novel 3-way alternating regression (3-AR) method as an effective strategy for the estimation of parameter values in S-distributions from frequency data. The 3-AR algorithm is very fast and performs well for error-free distributions and artificial noisy data obtained as random samples generated from S-distributions, as well as for traditional statistical distributions and for actual observation data. In rare cases where the algorithm does not immediately converge, its enormous speed...
Parameter estimation of sub-Gaussian stable distributions
In this paper, we present a parameter estimation method for sub-Gaussian stable distributions. Our algorithm has two phases: in the first phase, we calculate the average values of harmonic functions of observations and in the second phase, we conduct the main procedure of asymptotic maximum likelihood where those average values are used as inputs. This implies that the main procedure of our method does not depend on the sample size of observations. The main idea of our method lies in representing...
Parameterization and R-peak error estimations of ECG signals using independent component analysis.
Parametric and nonparametric empirical regression models: case study of copper bromide laser generation.
Parametric estimation of the regression function in a nonlinear model. (Estimación paramétrica de la función de regresión en un modelo no lineal.)
Parametric inference for mixed models defined by stochastic differential equations
Non-linear mixed models defined by stochastic differential equations (SDEs) are considered: the parameters of the diffusion process are random variables and vary among the individuals. A maximum likelihood estimation method based on the Stochastic Approximation EM algorithm, is proposed. This estimation method uses the Euler-Maruyama approximation of the diffusion, achieved using latent auxiliary data introduced to complete the diffusion process between each pair of measurement instants. A tuned...
Parametric test for change in a parameter occurring in the density of one-parameter exponential family
The problem of testing hypothesis under which the observations are independent, identically distributed against a class of alternatives of regression in a parameter of the one-parameter exponential family is studied. A parametric test for this problem is suggested. The relative efficiency of the parametric test compared to the rank test proposed in the author's preceding paper is also derived.
Paramétrisation et analyse des correspondances
Parametrization and geometric analysis of coordination controllers for multi-agent systems
In this paper, we address distributed control structures for multi-agent systems with linear controlled agent dynamics. We consider the parametrization and related geometric structures of the coordination controllers for multi-agent systems with fixed topologies. Necessary and sufficient conditions to characterize stabilizing consensus controllers are obtained. Then we consider the consensus for the multi-agent systems with switching interaction topologies based on control parametrization.