Mixed model for interoccurrence times of earthquakes based on the expectation-maximization algorithm

2011 ◽  
Vol 59 (5) ◽  
pp. 872-890 ◽  
Author(s):  
Nadia Tahernia ◽  
Morteza Khodabin ◽  
Noorbakhsh Mirzaei
Keyword(s):  
Expectation Maximization ◽  
Mixed Model ◽  
Expectation Maximization Algorithm

scholarly journals Improved Expectation Maximization Algorithm for Gaussian Mixed Model Using the Kernel Method

2013 ◽  
Vol 2013 ◽  
pp. 1-9
Author(s):  
Mohd Izhan Mohd Yusoff ◽  
Ibrahim Mohamed ◽  
Mohd Rizam Abu Bakar
Keyword(s):  
Expectation Maximization ◽  
Mixed Model ◽  
Likelihood Function ◽  
Kernel Method ◽  
Expectation Maximization Algorithm ◽  
Information Criteria ◽  
Maximum Likelihood Estimates ◽  
Modified Method ◽  
Telecommunication Companies ◽  
Future Work

Fraud activities have contributed to heavy losses suffered by telecommunication companies. In this paper, we attempt to use Gaussian mixed model, which is a probabilistic model normally used in speech recognition to identify fraud calls in the telecommunication industry. We look at several issues encountered when calculating the maximum likelihood estimates of the Gaussian mixed model using an Expectation Maximization algorithm. Firstly, we look at a mechanism for the determination of the initial number of Gaussian components and the choice of the initial values of the algorithm using the kernel method. We show via simulation that the technique improves the performance of the algorithm. Secondly, we developed a procedure for determining the order of the Gaussian mixed model using the log-likelihood function and the Akaike information criteria. Finally, for illustration, we apply the improved algorithm to real telecommunication data. The modified method will pave the way to introduce a comprehensive method for detecting fraud calls in future work.

scholarly journals A Harmonic Impedance Estimation Method Based on the Cauchy Mixed Model

2020 ◽  
Vol 2020 ◽  
pp. 1-13 ◽  
Author(s):  
Zhirong Tang ◽  
Huaqiang Li ◽  
Fangwei Xu ◽  
Qin Shu ◽  
Yue Jiang
Keyword(s):  
Expectation Maximization ◽  
Mixed Model ◽  
Expectation Maximization Algorithm ◽  
Data Distribution ◽  
Estimation Method ◽  
Measured Data ◽  
Estimation Methods ◽  
Accurate Estimation ◽  
Point Of Common Coupling ◽  
Common Coupling

In this paper, a new method without any tradition assumption to estimate the utility harmonic impedance of a point of common coupling (PCC) is proposed. But, the existing estimation methods usually are built on some assumptions, such as, the background harmonic is stable and small, the harmonic impedance of the customer side is much larger than that of utility side, and the harmonic sources of both sides are independent. However these assumptions are unpractical to modern power grid, which causes very wrong estimation. The proposed method first uses a Cauchy Mixed Model (CMM) to express the Norton equivalent circuit of the PCC because we find that the CMM can right fit the statistical distribution of the measured harmonic data for any PCC, by testing and verifying massive measured harmonic data. Also, the parameters of the CMM are determined by the expectation maximization algorithm (EM), and then the utility harmonic impedance is estimated by means of the CMM’s parameters. Compared to the existing methods, the main advantages of our method are as follows: it can obtain the accurate estimation results, but it is no longer dependent of any assumption and is only related to the measured data distribution. Finally, the effectiveness of the proposed method is verified by simulation and field cases.

Ordered subset expectation maximization algorithm for image reconstruction applied to zero-flow or low-flow mimicking brain phantom

2005 ◽  
Vol 25 (1_suppl) ◽  
pp. S678-S678
Author(s):  
Yasuhiro Akazawa ◽  
Yasuhiro Katsura ◽  
Ryohei Matsuura ◽  
Piao Rishu ◽  
Ansar M D Ashik ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Expectation Maximization ◽  
Expectation Maximization Algorithm ◽  
Low Flow ◽  
Brain Phantom ◽  
Zero Flow

scholarly journals Environmental Sensitivity and Awareness as Differentiating Factors in the Purchase Decision-Making Process in the Smartphone Industry—Case of Polish Consumers

2021 ◽  
Vol 13 (1) ◽  
pp. 348
Author(s):  
Lukasz Skowron ◽  
Monika Sak-Skowron
Keyword(s):  
Expectation Maximization ◽  
Cross Validation ◽  
Expectation Maximization Algorithm ◽  
Decision Making Process ◽  
Environmental Sensitivity ◽  
Significance Level ◽  
On Line ◽  
Purchase Process ◽  
The Impact ◽  
Fold Cross Validation

The first of the research objectives discussed in this article was to analyze the differences related to the valuation of particular factors influencing the purchase process in the smartphone industry, expressed by respondents with different sensitivity and environmental awareness, as well as the assessment of their knowledge about the impact of smartphones on the natural environment. The second objective of the research was to determine whether the level of environmental sensitivity, awareness and knowledge about the impact of smartphones on the environment has a statistically significant influence on the respondents’ choice of smartphone brand. The survey was conducted using an on-line questionnaire, distributed by a specialized research agency on a representative sample of over 1000 Polish residents. In order to identify the various customers clusters, the expectation-maximization algorithm and the v-fold cross-validation were used. Additionally, in order to analyze the significance level of differences between clusters the nonparametric Mann-Whitney U-test was carried out. The results show unequivocally that people with a different approach to ecological issues demonstrate statistically significant differences in their purchasing behaviors in the smartphone industry. Furthermore, it was noticed that in the case of comparing some smartphones brands, there is a statistically confirmed difference in the environmental sensitivity and awareness of the customers who use them. Moreover, the research has shown that in Polish customers’ consciousness smartphones are mistakenly considered to be relatively safe and environmentally friendly products.

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