The Pricing Problem

1987 ◽  
Vol 1 (3) ◽  
pp. 349-366
Author(s):  
Jaxk H. Reeves ◽  
Ashim Mallik ◽  
William P. McCormick
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
High Efficiency ◽  
Asymptotic Properties ◽  
Likelihood Estimation ◽  
Small Sample ◽  
Sequential Procedure ◽  
Pricing Scheme ◽  
Simulation Results ◽  
Small Sample Sizes

A sequential procedure to select optimal prices based on maximum likelihood estimation is considered. Asymptotic properties of the pricing scheme and the concommitant estimation problem are examined. For small sample sizes, simulation results show that the proposed procedure has high efficiency relative to the best procedure when the parameter is known.

Maximum Likelihood Estimation for MA(1) Processes with a Root on or near the Unit Circle

1996 ◽  
Vol 12 (1) ◽  
pp. 1-29 ◽  
Author(s):  
Richard A. Davis ◽  
William T.M. Dunsmuir
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Unit Circle ◽  
Asymptotic Distribution ◽  
Moving Average ◽  
Likelihood Estimation ◽  
Small Sample ◽  
Practical Significance ◽  
True Parameter ◽  
Small Sample Sizes

This paper considers maximum likelihood estimation for the moving average parameter θ in an MA(1) model when θ is equal to or close to 1. A derivation of the limit distribution of the estimate θLM, defined as the largest of the local maximizers of the likelihood, is given here for the first time. The theory presented covers, in a unified way, cases where the true parameter is strictly inside the unit circle as well as the noninvertible case where it is on the unit circle. The asymptotic distribution of the maximum likelihood estimator subMLE is also described and shown to differ, but only slightly, from that of θLM. Of practical significance is the fact that the asymptotic distribution for either estimate is surprisingly accurate even for small sample sizes and for values of the moving average parameter considerably far from the unit circle.

Study on Optimization of the Number of DF Stations

2014 ◽  
Vol 709 ◽  
pp. 485-490
Author(s):  
Xiang Wu ◽  
Jun Jun Zong ◽  
Xun Xue Cui ◽  
Chuan Xu Liu
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Direction Finding ◽  
Location Error ◽  
Location Accuracy ◽  
Error Models ◽  
Reasonable Number ◽  
Simulation Results

Reasonable number of direction finding station is examined in multi-station bearing-crossing location. Though it is believed that increasing the number of station is helpful to improve the location accuracy, In the paper, the maximum likelihood estimation (MLE) as an example. The algorithms and the location error models are given. The simulation results show that the location accuracy will be improved quickly with the increase of the number of the measuring participants, but the improvement will be sharply slowed down if too many station involved, which also boost the complexity of location.

scholarly journals Quantifying the strength of general factors in psychopathology: A comparison of CFA with maximum likelihood estimation, BSEM and ESEM/EFA bi-factor approaches

2018 ◽  
Author(s):  
Aja Louise Murray ◽  
Tom Booth ◽  
Manuel Eisner ◽  
Ingrid Obsuth ◽  
Denis Ribeaud
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Factor Models ◽  
General Factor ◽  
Normative Sample ◽  
Ml Estimation ◽  
Co Morbidity ◽  
Simulation Results ◽  
P Factor

Whether or not importance should be placed on an all-encompassing general factor of psychopathology (or p-factor) in classifying, researching, diagnosing and treating psychiatric disorders depends (amongst other issues) on the extent to which co-morbidity is symptom-general rather than staying largely within the confines of narrower trans-diagnostic factors such as internalising and externalising. In this study we compared three methods of estimating p-factor strength. We compared omega hierarchical and ECV calculated from CFA bi-factor models with maximum likelihood (ML) estimation, from ESEM/EFA models with a bifactor rotation, and from BSEM bi-factor models. Our simulation results suggested that BSEM with small variance priors on secondary loadings may be the preferred option. However, CFA with ML also performed well provided secondary loadings were modelled We provide two empirical examples of applying the three methodologies using a normative sample of youth (z-proso, n=1286) and University counselling sample (n= 359).

An Image Restoration Method for Earthquake Ruin Scene

2013 ◽  
Vol 321-324 ◽  
pp. 1107-1110
Author(s):  
Yan Xing Song ◽  
Jing Song Yang ◽  
Qin Gao ◽  
Shu Cong Liu
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Image Restoration ◽  
Estimation Method ◽  
Operation Time ◽  
Likelihood Estimation ◽  
Simulation Results ◽  
Restoration Method ◽  
Maximum Likelihood Estimation Method

An image restoration method for earthquake ruin scene is proposed in this paper. This method uses maximum likelihood estimation method based on Poisson (PMLE). This algorithm is introduced at first, then an image of earthquake ruin scene is processed with this image restoration method. Simulation results show that iterations in this method will effect the PSNR of the processed image and operation time, and this method can restore image of earthquake ruin scene effectively and has a good practicability.

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