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A Batch Means Methodology for Estimation of a Nonlinear Function of a Steady- State Mean
Simulation Output Analysis Steady-State Simulation Nonlinear Estimation Batch Means Jack- knifing
2015/7/8
We study the estimation of steady-state performance measures from an Ad-valued stochastic process Y = {Y(t): t≥0} representing the output of a simulation. In many applications, we may be interested in...
Estimation of Stationary Densities for Markov Chains
Estimation Stationary Densities Markov Chains
2015/7/8
We describe a new estimator of the stationary density of a Markov chain on general state space. The new estimator is easier to compute, converges faster, and empirically gives visually superior estima...
On the Validity of Long-Run Estimation Methods for Discrete-Event Systems
Validity Long-Run Estimation Methods Discrete-Event Systems
2015/7/8
On the Validity of Long-Run Estimation Methods for Discrete-Event Systems.
Estimation of Continuous-time Markov Processes Sampled at Random Time Intervals
Method of moments parameter estimation Markov process
2015/7/6
We introduce a family of generalized-method-of-moments estimators of the parameters of a continuous-time Markov process observed at random time intervals. The results include strong consistency, asymp...
Simulation-based Parameter Estimation for Complex Models: A Breast Cancer Natural History Modelling Illustration
Simulation-based Parameter Estimation Complex Models Breast Cancer Natural History Modelling Illustration
2015/7/6
Simulation-based parameter estimation offers a powerful means of estimating parameters in complex stochastic models. We illustrate the application of these ideas in the setting of a natural history mo...
Simulation-based Response Surface Estimation in the Presence of Monotonicity
Simulation-based Response Surface Estimation Presence Monotonicity
2015/7/6
In many stochastic models, it is known that the response surface corresponding to a particular performance measure is monotone in the underlying parameter. For example, the steady-state mean waiting t...
In this paper, we introduce a new approach to constructing unbiased estimators when computing expectations of path functionals associated with stochastic differential equations (SDEs). Our randomizati...
The Cross-Entropy Method for Estimation
cross-entropy estimation rare events importance sampling adaptive Monte Carlo zero-variance distribution
2015/7/6
This chapter describes how difficult statistical estimation problems can often be solved efficiently by means of the cross-entropy (CE) method. The CE method can be viewed as an adaptive importance sa...
Unbiased Estimation with Square Root Convergence for SDE Models
Unbiased Estimation Square Root Convergence SDE Models
2015/7/6
In many settings in which Monte Carlo methods are applied, there may be no known algorithm for exactly generating the random object for which an expectation is to be computed. Frequently, however, one...
Exact Estimation for Markov Chain Equilibrium Expectations
Exact Estimation Markov Chain Equilibrium Expectations
2015/7/6
We introduce a new class of Monte Carlo methods, which we call exact estimation algorithms. Such algorithms provide unbiased estimators for equilibrium expectations associated with real-valued functio...
LEAST SQUARES ESTIMATION OF DISCRETE LINEAR DYNAMIC SYSTEMS USING ORTHOGONAL TRANSFORMATIONS
DISCRETE LINEAR DYNAMIC SYSTEMS ORTHOGONAL TRANSFORMATIONS
2015/7/3
Kalman [9] introduced a method for estimating the state of a discrete linear dynamic
system subject to noise. His method is fast but has poor numerical properties. Duncan and Horn [3]
showed that th...
The Dantzig selector:statistical estimation when p is much larger than n
Statistical linear model model selection ideal estimation oracle inequalities sparse solutions to underdetermined systems `1-minimization linear programming restricted orthonormality geometry in high dimensions random matrices
2015/6/17
In many important statistical applications, the number of variables or parameters p is much larger than the number of observations n. Suppose then that we have observations y = Xβ + z, where β ∈ Rp is...
Modern statistical estimation via oracle inequalities
Modern statistical estimation oracle inequalities
2015/6/17
A number of fundamental results in modern statistical theory involve thresholding estimators. This survey paper aims at reconstructing the history of how thresholding rules came to be popular in stati...
REJOINDER: THE DANTZIG SELECTOR:STATISTICAL ESTIMATION WHEN P IS MUCH LARGER THAN N
DANTZIG SELECTOR STATISTICAL ESTIMATION MUCH LARGER THAN N
2015/6/17
First of all, we would like to thank all the discussants for their interest and comments, as well as for their thorough investigation. The comments all underlie the importance and timeliness of the to...
Supplementary materials for Statistical Estimation and Testing via the Sorted 1 Norm
Supplementary materials Statistical Estimation Sorted 1 Norm
2015/6/17
In this note we give a proof showing that even though the number of false discoveries and the total number of discoveries are not continuous functions of the parameters, the formulas we obtain for the...