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A note on the estimation of degree of differencing in long memory time series analysis
the estimation of degree long memory time series analysis
2009/9/23
In this paper we investigate the properties of the
estimator of degree of differencing the fractional d in long memory
time series analysis via consistent spectral density estimation. It is
shown t...
Computational Methods for Parameter Estimation in Climate Models
Parametric Uncertainties InverseProblems SimulatedAnnealing Climate Models
2009/9/22
Intensive computational methods have been used by Earth scientists
in a wide range of problems in data inversion and uncertainty quantication such
as earthquake epicenter location and climate projec...
Bayesian estimation of the basic reproduction number in stochastic epidemic models
Basic reproduction number Bayesian inference Epidemics Linear programming Stochastic epidemic models
2009/9/22
Our main focus is on the basic reproduction number, a quantity
of central importance in mathematical epidemic theory, whose value essentially
dictates whether or not a large epidemic outbreak can oc...
EM versus Markov chain Monte Carlo for estimation of hidden Markov models: a computational perspective
hidden Markov model incomplete data missing data EM trans-dimensional Monte Carlo computational statistics
2009/9/22
Hidden Markov models (HMMs) and related models have become stan-
dard in statistics during the last 15C2 years, with applications in diverse areas
like speech and other statistical signal processing...
M-estimation for linear regression with infinite variance
M-estimation linear regression infinite variance
2009/9/22
The limiting behavior of M-estimates for a Iinear model
when the regressors and/or errors have heavy tailed distributions is
given. By hermy toil we mean that the distribution is in the domain of
a...
Une etude algebrique de l'admissibilite en estimation lineaire de la moyenne sur un modele general de Gauss-Markov
etude algebrique estimation lineaire Gauss-Markov
2009/9/22
It would appear useful to come back to the question of
admissibility in imear estimation on a general Gauss-Markov model.
We prove how a functional approach to this problem, based on a very
importa...
Bayesian Dynamic Density Estimation
Dependent Dirichlet process Nonparametric Bayes Random probability measure Travel Costs Insurance Claim Distributions
2009/9/22
Empirical distributions in nance and economics might show heavy
tails, volatility clustering, varying mean returns and multimodality as part of their
features. However, most statistical models avail...
Estimation of Faraday Rotation Measures of the Near Galactic Sky Using Gaussian Process Models
Markov chain Monte Carlo Gaussian process error mixture model spatial model
2009/9/22
Our primary goal is to obtain a smoothed summary estimate of the
magnetic eld generated in and near to the Milky Way by using Faraday rotation
measures (RMs) Each RM in our data set provides an inte...
Nonparametric Estimation of Kullback-Leibler Information Illustrated by Evaluating Goodness of Fit
Goodness of Fit Kullback-Leibler Information Consistency
2009/9/22
We describe a method for quantifying the lack of t in a proposed
family of distributions. The method involves estimating the posterior distribu-
tion of the Kullback-Leibler information between the ...
On estimation in the multiplicative intensity model via histogram sieve
Point processes multiplicative intensity model sieve method of estimation
2009/9/21
In the paper we consider the problem of estimating
stochastic intensity of a point process from multiplicative intensity
model using the method of sieves of Grenander [6]. Basic properties of
the h...
Adaptive estimation of hazard functions
Adaptive estimation sieved maximum likelihood neural nets structural risk minimization
2009/9/21
In this paper we obtain convergence rates for sieved
maximum-likelihood &timators of the log-hazard function in a censoring
model. We also establish convergence results for an adaptive
version of t...
On adaptive estimation based on ranks in ARMA processes
Local asymptotic normality (LAN) asymptotic linearity locally asymptotically minimax (LAM)
2009/9/21
This paper describe6 the adaptive estimation problem
based on ranks for the parameter of an ARMA process. Tbe local
asymptotic normality property with a ranked based central sequence
allows for the...
The use of variable kernel mass in density estimation
variable kernel mass density estimation
2009/9/21
The use of variable kernel mass in density estimation。
Gaussian semiparametric estimation for random fields with singular spectrum
Discrete Fourier transforms random fields singular spectrum Whittle semiparametric estimates
2009/9/21
We analyze the asymptotic behaviour of the tapered
discrete Fourier transforms far random fields with singular spectrum.
The results are used to establish consistency and asymptotic normality
for s...
Bayesian nonparametric estimation of the radiocarbon calibration curve
Gaussian process archaeology chronology building cross-validation
2009/9/21
The process of calibrating radiocarbon determinations onto the cal-
endar scale involves, as a rst stage, the estimation of the relationship between
calendar and radiocarbon ages (the radiocarbon ca...