Survival Analysis Competing Risk using Fine-Gray Subdistribution Model with the Maximum Partial Likelihood Estimation Method

This article examines the impact of institutional quality on bilateral trade flow between Malaysia and selected 25 African Organisation of Islamic Cooperation (OIC) member countries. Four institutional qualities were selected from World Governance Indicators with other trade predictors from the period from 1985 to 2016. Using gravity model of trade and Poisson pseudo-maximum likelihood estimation method (PPML) technique, the results confirm that government effectiveness, regulatory quality and political stability have an adverse effect on bilateral trade flow among the OIC countries in Africa. On the other hand, these institutional quality variables were considered as a strength for Malaysian economic growth. Therefore, better institutional quality reforms are needed among OIC member countries in Africa in order to accelerate trade, economic growth and development in their region.

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A multi-group higher-order factor analysis for studying the gender-effect in Teacher Job Satisfaction

METRON ◽

10.1007/s40300-021-00204-x ◽

2021 ◽

Author(s):

Carlo Cavicchia ◽

Pasquale Sarnacchiaro

Keyword(s):

Job Satisfaction ◽

Factor Analysis ◽

Secondary School Teachers ◽

Estimation Method ◽

Likelihood Estimation ◽

Higher Order ◽

Teacher Job Satisfaction ◽

Public Secondary School ◽

Order Factor ◽

Maximum Likelihood Estimation Method

AbstractTeachers’ performances also depend on whether and how they are satisfied with their job. Therefore, Teacher Job Satisfaction must be considered as the driver of teachers’ accomplishments. To plan future policies and improve the overall teaching process, it is crucial to understand which factors mostly contribute to Teacher Job Satisfaction. A Common Assessment Framework and Education questionnaire was administered to 163 Italian public secondary school teachers to collect data, and a second-order factor analysis was used to detect which factors impact on Teacher Job Satisfaction, and to what extent. This model-based approach guarantees to detect factors which respect important properties: unidimensionality and reliability. All the coefficients are estimated according to the maximum likelihood estimation method in order to make inference on the parameters and on the validity of the model. Moreover, a new multi-group test for higher-order factor analysis was proposed and implemented. Finally, we analyzed in detail whether the factors impacting Teacher Job Satisfaction are characterized by gender.

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SiFi

ACM Transactions on Internet of Things ◽

10.1145/3450567 ◽

2021 ◽

Vol 2 (3) ◽

pp. 1-21

Author(s):

Deke Guo ◽

Xiaoqiang Teng ◽

Yulan Guo ◽

Xiaolei Zhou ◽

Zhong Liu

Keyword(s):

Rapid Development ◽

Estimation Method ◽

Likelihood Estimation ◽

Location Based Services ◽

Shopping Mall ◽

Inference Problem ◽

Indoor Location ◽

Label Semantics ◽

Geometrical Constraints ◽

Indoor Scenes

Due to the rapid development of indoor location-based services, automatically deriving an indoor semantic floorplan becomes a highly promising technique for ubiquitous applications. To make an indoor semantic floorplan fully practical, it is essential to handle the dynamics of semantic information. Despite several methods proposed for automatic construction and semantic labeling of indoor floorplans, this problem has not been well studied and remains open. In this article, we present a system called SiFi to provide accurate and automatic self-updating service. It updates semantics with instant videos acquired by mobile devices in indoor scenes. First, a crowdsourced-based task model is designed to attract users to contribute semantic-rich videos. Second, we use the maximum likelihood estimation method to solve the text inferring problem as the sequential relationship of texts provides additional geometrical constraints. Finally, we formulate the semantic update as an inference problem to accurately label semantics at correct locations on the indoor floorplans. Extensive experiments have been conducted across 9 weeks in a shopping mall with more than 250 stores. Experimental results show that SiFi achieves 84.5% accuracy of semantic update.

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Calibration Analysis of High-G MEMS Accelerometer Sensor Based on Wavelet and Wavelet Packet Denoising

Sensors ◽

10.3390/s21041231 ◽

2021 ◽

Vol 21 (4) ◽

pp. 1231

Author(s):

Yunbo Shi ◽

Juanjuan Zhang ◽

Jingjing Jiao ◽

Rui Zhao ◽

Huiliang Cao

Keyword(s):

Wavelet Packet ◽

Estimation Method ◽

Likelihood Estimation ◽

Parameter Extraction ◽

Accelerometer Sensor ◽

Oscillation Phase ◽

Mems Accelerometer ◽

Optimal Tree ◽

Adaptive Decomposition ◽

Entropy Criterion

High-G accelerometers are mainly used for motion measurement in some special fields, such as projectile penetration and aerospace equipment. This paper mainly explores the wavelet threshold denoising and wavelet packet threshold denoising in wavelet analysis, which is more suitable for high-G piezoresistive accelerometers. In this paper, adaptive decomposition and Shannon entropy criterion are used to find the optimal decomposition layer and optimal tree. Both methods use the Stein unbiased likelihood estimation method for soft threshold denoising. Through numerical simulation and Machete hammer test, the wavelet threshold denoising is more suitable for the dynamic calibration of a high-G accelerometer. The wavelet packet threshold denoising is more suitable for the parameter extraction of the oscillation phase.

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Research on the Distributed Characteristics of the Delay for Network Coding Based Real-Time Multicast in MANETs

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.530-531.768 ◽

2014 ◽

Vol 530-531 ◽

pp. 768-772

Author(s):

Guo Ping Tan ◽

Lin Feng Tan ◽

Lei Cao ◽

Mei Yan Ju

Keyword(s):

Maximum Likelihood ◽

Probability Distribution ◽

Network Coding ◽

Real Time ◽

Lognormal Distribution ◽

Ad Hoc ◽

Estimation Method ◽

Likelihood Estimation ◽

Actual Distribution ◽

Delay Distribution

For the study of the applications of partial network coding based real-time multicast protocol (PNCRM) in Mobile Ad hoc networks, the researches should be developed in the probability distribution of delay. In this paper, NS2 is used to obtain the delay of data packets through simulations. Because the delay does not obey the strict normal distribution, the maximum likelihood estimate method based on the lognormal distribution is used to process the data. Using MATLAB to obtain the actual distribution of the natural logarithm of delay, then drawing the delay distribution with the maximum likelihood estimation method based on the lognormal distribution, the conclusion that the distributions obtained by the above mentioned methods are basically consistent can be obtained. So the delay distribution of PNCRM meets the lognormal distribution and the characteristic of delay probability distribution can be estimated.

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The Weibull Birnbaum-Saunders Distribution And Its Applications

Statistics Optimization & Information Computing ◽

10.19139/soic-2310-5070-887 ◽

2020 ◽

Vol 9 (1) ◽

pp. 61-81

Author(s):

Lazhar BENKHELIFA

Keyword(s):

Maximum Likelihood ◽

Estimation Method ◽

Likelihood Estimation ◽

Real Data ◽

Reliability Estimation ◽

Maximum Likelihood Estimates ◽

Model Parameters ◽

Data Sets ◽

Proposed Model ◽

Modeling Data

A new lifetime model, with four positive parameters, called the Weibull Birnbaum-Saunders distribution is proposed. The proposed model extends the Birnbaum-Saunders distribution and provides great flexibility in modeling data in practice. Some mathematical properties of the new distribution are obtained including expansions for the cumulative and density functions, moments, generating function, mean deviations, order statistics and reliability. Estimation of the model parameters is carried out by the maximum likelihood estimation method. A simulation study is presented to show the performance of the maximum likelihood estimates of the model parameters. The flexibility of the new model is examined by applying it to two real data sets.

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Modelling Hedge Fund Indices Using Levy Processes

10.32920/ryerson.14654616.v1 ◽

2021 ◽

Author(s):

Ugochi T. Emenogu

Keyword(s):

Hedge Funds ◽

Value At Risk ◽

Lévy Processes ◽

Hedge Fund ◽

Estimation Method ◽

Likelihood Estimation ◽

Levy Processes ◽

Empirical Characteristic Function ◽

Empirical Comparison ◽

Double Exponential

In this thesis, the use of Levy processes to model the dynamics of Hedge fund indices is proposed. Merton (1976) and Kou (2002) models which differ on the specifcation of the jump components are employed to model hedge funds in continuous time. Secondly, an alternative to the Maximum Likelihood Estimation (MLE) method, Empirical Characteristic Function (ECF) estimation method, is explored in our analysis and compared to MLE. The Cumulant Matching Method (CMM) is used in getting the starting parameters; and the method that overcomes the major problem associated with this estimation method is outlined. Calibration shows that these two models t the data well, however, the empirical comparison shows that double exponential jumps are more consistent with the empirical data. Each fund's exposure to risk is calculated using Monte Carlo Value-at-Risk (VaR) estimation method.

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The modified beta transmuted family of distributions with applications using the exponential distribution

PLoS ONE ◽

10.1371/journal.pone.0258512 ◽

2021 ◽

Vol 16 (11) ◽

pp. e0258512

Author(s):

Phillip Oluwatobi Awodutire ◽

Oluwafemi Samson Balogun ◽

Akintayo Kehinde Olapade ◽

Ethelbert Chinaka Nduka

Keyword(s):

Exponential Distribution ◽

Real Life ◽

Estimation Method ◽

Likelihood Estimation ◽

Life Time ◽

Time Data ◽

New Family ◽

Special Cases ◽

The Family ◽

Family Of Distributions

In this work, a new family of distributions, which extends the Beta transmuted family, was obtained, called the Modified Beta Transmuted Family of distribution. This derived family has the Beta Family of Distribution and the Transmuted family of distribution as subfamilies. The Modified beta transmuted frechet, modified beta transmuted exponential, modified beta transmuted gompertz and modified beta transmuted lindley were obtained as special cases. The analytical expressions were studied for some statistical properties of the derived family of distribution which includes the moments, moments generating function and order statistics. The estimates of the parameters of the family were obtained using the maximum likelihood estimation method. Using the exponential distribution as a baseline for the family distribution, the resulting distribution (modified beta transmuted exponential distribution) was studied and its properties. The modified beta transmuted exponential distribution was applied to a real life time data to assess its flexibility in which the results shows a better fit when compared to some competitive models.

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The Weibull Generalized Exponential Distribution with Censored Sample: Estimation and Application on Real Data

Complexity ◽

10.1155/2021/6653534 ◽

2021 ◽

Vol 2021 ◽

pp. 1-15

Author(s):

Hisham M. Almongy ◽

Ehab M. Almetwally ◽

Randa Alharbi ◽

Dalia Alnagar ◽

E. H. Hafez ◽

...

Keyword(s):

Monte Carlo ◽

Exponential Distribution ◽

Estimation Method ◽

Interval Estimation ◽

Likelihood Estimation ◽

Real Data ◽

Mcmc Methods ◽

Generalized Exponential Distribution ◽

Censored Sample ◽

Sample Maximum

This paper is concerned with the estimation of the Weibull generalized exponential distribution (WGED) parameters based on the adaptive Type-II progressive (ATIIP) censored sample. Maximum likelihood estimation (MLE), maximum product spacing (MPS), and Bayesian estimation based on Markov chain Monte Carlo (MCMC) methods have been determined to find the best estimation method. The Monte Carlo simulation is used to compare the three methods of estimation based on the ATIIP-censored sample, and also, we made a bootstrap confidence interval estimation. We will analyze data related to the distribution about single carbon fiber and electrical data as real data cases to show how the schemes work in practice.

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ESTIMASI PARAMETER PADA MODEL COX MULTIVARIAT DENGAN METODE MAXIMUM PARTIAL LIKELIHOOD ESTIMATION

Jurnal Ilmiah Matematika dan Pendidikan Matematika ◽

10.20884/1.jmp.2012.4.1.2954 ◽

2012 ◽

Vol 4 (1) ◽

pp. 185

Author(s):

Irfan Wahyudi ◽

Purhadi Purhadi ◽

Sutikno Sutikno ◽

Irhamah Irhamah

Keyword(s):

Parameter Estimation ◽

Likelihood Function ◽

Cox Model ◽

Hessian Matrix ◽

Likelihood Estimation ◽

Partial Likelihood ◽

Estimation Methods ◽

Hazard Functions ◽

Score Vector ◽

Parameter Estimation Methods

Multivariate Cox proportional hazard models have ratio property, that is the ratio of hazard functions for two individuals with covariate vectors z1 and z2 are constant (time independent). In this study we talk about estimation of prameters on multivariate Cox model by using Maximum Partial Likelihood Estimation (MPLE) method. To determine the appropriate estimators that maximize the ln-partial likelihood function, after a score vector and a Hessian matrix are found, numerical iteration methods are applied. In this case, we use a Newton Raphson method. This numerical method is used since the solutions of the equation system of the score vector after setting it equal to zero vector are not closed form. Considering the studies about multivariate Cox model are limited, including the parameter estimation methods, but the methods are urgently needed by some fields of study related such as economics, engineering and medical sciences. For this reasons, the goal of this study is designed to develop parameter estimation methods from univariate to multivariate cases.

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