Search results for "Maximization"
showing 10 items of 84 documents
Forecasting time series with missing data using Holt's model
2009
This paper deals with the prediction of time series with missing data using an alternative formulation for Holt's model with additive errors. This formulation simplifies both the calculus of maximum likelihood estimators of all the unknowns in the model and the calculus of point forecasts. In the presence of missing data, the EM algorithm is used to obtain maximum likelihood estimates and point forecasts. Based on this application we propose a leave-one-out algorithm for the data transformation selection problem which allows us to analyse Holt's model with multiplicative errors. Some numerical results show the performance of these procedures for obtaining robust forecasts.
Una solucion bayesiana a la Paradoja de Stein
1982
If we are interested in making inferences about the square norm of the mean in a multivariate normal model, the usual uniform prior for the mean is not sound, as revealed by Stein in his 1959 work. This paper studies in what sense this prior must be modified by using the maximization of missing information procedure (Bernardo, 1979)
Maximum likelihood estimation for the exponential power function parameters
1995
This paper addresses the problem of obtaining maximum likelihood estimates for the three parameters of the exponential power function; the information matrix is derived and the covariance matrix is here presented; the regularity conditions which ensure asymptotic normality and efficiency are examined. A numerical investigation is performed for exploring the bias and variance of the maximum likelihood estimates and their dependence on sample size and shape parameter.
Sample Size Requirements of a Mixture Analysis Method with Applications in Systematic Biology
1999
The available information on sample size requirements of mixture analysis methods is insufficient to permit a precise evaluation of the potential problems facing practical applications of mixture analysis. We use results from Monte Carlo simulation to assess the sample size requirements of a simple mixture analysis method under conditions relevant to biological applications of mixture analysis. The mixture model used includes two univariate normal components with equal variances but assumes that the researcher is ignorant as to the equality of the variances. The method used relies on the EM algorithm to compute the maximum likelihood estimates of the mixture parameters, and the likelihood r…
An approximation to maximum likelihood estimates in reduced models
1990
SUMMARY An approximation to the maximum likelihood estimates of the parameters in a model can be obtained from the corresponding estimates and information matrices in an extended model, i.e. a model with additional parameters. The approximation is close provided that the data are consistent with the first model. Applications are described to log linear models for discrete data, to models for multivariate normal distributions with special covariance matrices and to mixed discrete-continuous models.
Profit Margin Ratio, Markup, Profit Margin Per Unit, Economic Profit, and Profitability as Objectives for the Firm: An Economic Point-of-View
2015
We study five operational objectives for the firm: three marketing objectives (maximizing profit-margin ratio, maximizing markup, and maximizing profit-margin-per-unit), and two financial objective (maximizing economic profit (i.e., EVA) and maximizing profitability), as alternatives to the scholarly objective of maximizing profit. We prove that (i) Sales are lowest for profit-margin-per-unit, intermediate for profit-margin ratio and markup, and highest for profit maximization. Input consumption, including labor, is lower. Prices are in the reverse order. In terms of profit, profit-margin ratio, markup, and profit-margin-per-unit are necessarily less efficient than the classical profit maxi…
A reconsideration of the link between vertical externality and managerial incentives
2018
Previous research revealed that the strategic role of delegation contracts disappears if two quantity†setting firms outsource input production to a monopolistic supplier. I show that this role is restored if the assumption of a downstream duopoly is relaxed. Thus, delegation contracts allow downstream profit†maximizing owners to commit their firms to a behavior that differs from their preferences. This behavior varies nonmonotonically with the number of firms in the downstream market. Corresponding deviations from profit maximization are larger if the upstream monopolist makes a price precommitment. But little to no deviation occurs if the number of firms is large.
Numerical Optimization of Liner Impedance in Acoustic Duct
2020
Abstract The SALUTE project aims at evaluating performance of metacomposites for acoustic smart lining in grazing turbulent flow. Theoretical and numerical investigations are carried out for designing innovative specimen. A specific focus is placed in the realization of prototypes for evaluating the metacomposite liner performances in 2D and 3D liners, its process complexity and robustness. The insight gain in this project is new tools for obtaining innovative samples; the acoustical experimental tests demonstrate efficiency and robustness of such technology for controlling UHBR noise emission. This paper is focused on parametric study based on the maximization of the absorption coefficient…
Affinity Distributions of a Molecularly Imprinted Polymer Calculated Numerically by the Expectation-Maximization Method
2003
Affinity distributions are calculated from adsorption isotherm data obtained for the enantiomers of L- and D-phenylalanine anilide (PA) on native and thermally annealed polymers molecularly imprinted with L-PA. The calculation is obtained with an iterative algorithm called expectation-maximization that does not require prior fit of the data to an isotherm model before inversion and thus yields a distribution indicative of the data only. The results show bimodal distributions, suggestive of a two-site model describing relatively selective and nonselective adsorption modes of the L-enantiomer and a corresponding unimodal/nonselective adsorption mode for the D-enantiomer. The nonselective adso…
Transmission Optimization and Resource Allocation for Wireless Powered Dense Vehicle Area Network With Energy Recycling
2022
The wireless-powered communication paradigm brings self-sustainability to the on-vehicle sensors by harvesting the energy from radiated radio frequency (RF) signals. This paper proposes a novel transmission and resource allocation strategy for the scenario where multiple wireless powered vehicle area networks (VAN) co-existed with high density. The considered multi-VAN system consists of a remote master access point (MAP), multiple on-vehicle hybrid access points (HAPs) and sensors. Unlike previous works, we consider that the sensors can recycle the radiated radio frequency energy from all the HAPs when HAPs communicate with MAP, so the dedicated signals for energy harvesting (EH) are unnec…