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Properties of Census Dual System Population Size Estimators
Capture-recapture Correlation Bias Erroneous enumeration Kernel smooth- ing Model bias
2016/1/19
We evaluate three population size estimators, including the post-stratification and lo-gistic regression estimators which has been or will be implemented in the US Census dual system surveys. Conditio...
Maximum likelihood and generalized spatial two-stage least-squares estimators for a spatial-autoregressive model with spatial-autoregressive disturbances
spreg spatial-autoregressive models
2015/9/24
We describe the spreg command, which implements a maximum
likelihood estimator and a generalized spatial two-stage least-squares estimator
for the parameters of a linear cross-sectional spatial-auto...
Derandomizing and Rerandomizing Variance Estimators
Derandomizing Rerandomizing Variance Estimators
2015/7/8
This technical report is meant to accompany the paper [7] and should be read in conjuction with that work. It describes several concepts which were alluded to in [7] but not elaborated on.
We give al...
On the Small-Sample Optimality of Multiple-Regeneration Estimators
Small-Sample Optimality Multiple-Regeneration Estimators
2015/7/8
We describe a simulation output analysis methodology suitable for stochastic processes that are regenerative with respect to multiple regeneration sequences. Our method exploits this structure to cons...
One may consider a discrete-event simulation as a Markov chain evolving on a suitably rich state space. One way that regenerative cycles may be constructed for general state-space Markov chains is to ...
Empirical Performance of Bias-reducing Estimators for Regenerative Steady-State Simulations
Bias-reducing estimators regeneration simulation
2015/7/6
When simulating a stochastic system, simulationists often are interested in estimating various steady-state performance measures. The classical point estimator for such a measure involves simply takin...
On the Theoretical Comparison of Low-Bias Steady-State Estimators
Low-bias estimators steady-state simulation mean-square error expansion
2015/7/6
The time-average estimator is typically biased in the context of steady-state simulation, and its bias is of order 1/t, where t represents simulated time. Several “low-bias” estimators have been devel...
A Large Deviations View of Asymptotic Efficiency for Simulation Estimators
Large Deviations View Asymptotic Efficiency Simulation Estimators
2015/7/6
Consider a simulation estimator α(c) based on expending c units of computer time, to estimate a quantity α. One measure of efficiency is to attempt to minimize P(|α(c)−α|>ε) for large c. This he...
New Estimators for Parallel Steady-State Simulations
Estimators Parallel Steady-State Simulations
2015/7/6
When estimating steady-state parameters in parallel discrete event simulation, initial transient is an important issue to consider. To mitigate the impact of initial condition on the quality of the es...
Asymptotic Robustness of Estimators in Rare-Event Simulation
Asymptotic Robustness Estimators Rare-Event Simulation
2015/7/6
The asymptotic robustness of estimators as a function of a rarity parameter, in the context of rare-event simulation, is often qualified by properties such as bounded relative error (BRE) and logarith...
Zero-Variance Importance Sampling Estimators for Markov Process Expectations
Importance sampling Markov process simulation
2015/7/6
We consider the use of importance sampling to compute expectations of functionals of Markov processes. For a class of expectations that can be characterized as positive solutions to a linear system, w...
On model selection consistency of M-estimators with geometrically decomposable penalties
model selection consistency M-estimators geometrically decomposable penalties
2013/6/14
Penalized M-estimators are used in many areas of science and engineering to fit models with some low-dimensional structure in high-dimensional settings. In many problems arising in bioinformatics, sig...
Limit theorems for kernel density estimators under dependent samples
Kernel density estimator consistency convergence rate mixing rate
2013/6/14
In this paper, we construct a moment inequality for mixing dependent random variables, it is of independent interest. As applications, the consistency of the kernel density estimation is investigated....
Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
Regularized M-estimators nonconvexity Statistical algorithmic theory local optima
2013/6/14
We establish theoretical results concerning all local optima of various regularized M-estimators, where both loss and penalty functions are allowed to be nonconvex. Our results show that as long as th...
A General Family of Estimators for Estimating Population Mean in Systematic Sampling Using Auxiliary Information in the Presence of Missing Observations
Family of estimators Auxiliary information Mean square error Non-response Systematic sampling
2013/6/14
This paper proposes a general family of estimators for estimating the population mean in systematic sampling in the presence of non-response adapting the family of estimators proposed by Khoshnevisan ...