scholarly journals Symmetry Analysis of the Uncertain Alternative Box-Cox Regression Model

Symmetry ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 22
Author(s):  
Liang Fang ◽  
Zaiying Zhou ◽  
Yiping Hong
Keyword(s):  
Numerical Simulations ◽  
Least Squares ◽  
Linear Models ◽  
Cox Regression ◽  
Cox Model ◽  
Estimation Method ◽  
Likelihood Estimation ◽  
The Asymmetry ◽  
Box Cox Transformation ◽  
Theoretical Issues

The asymmetry of residuals about the origin is a severe issue in estimating a Box-Cox transformed model. In the framework of uncertainty theory, there are such theoretical issues regarding the least-squares estimation (LSE) and maximum likelihood estimation (MLE) of the linear models after the Box-Cox transformation on the response variables. Heretofore, only weighting methods for least-squares analysis have been available. This article proposes an uncertain alternative Box-Cox model to alleviate the asymmetry of residuals and avoid λ tending to negative infinity for uncertain LSE or uncertain MLE. Such symmetry of residuals about the origin is reasonable in applications of experts’ experimental data. The parameter estimation method was given via a theorem, and the performance of our model was supported via numerical simulations. According to the numerical simulations, our proposed ‘alternative Box-Cox model’ can overcome the problems of a grossly underestimated lambda and the asymmetry of residuals. The estimated residuals neither deviated from zero nor changed unevenly, in clear contrast to the LSE and MLE for the uncertain Box-Cox model downward biased residuals. Thus, though the LSE and MLE are not applicable on the uncertain Box-Cox model, they fit the uncertain alternative Box-Cox model. Compared with the uncertain Box-Cox model, the issue of a systematically underestimated λ is not likely to occur in our uncertain alternative Box-Cox model. Both the LSE and MLE can be used directly without constructing a weighted estimation method, offering better performance in the asymmetry of residuals.

scholarly journals 464Basics of survival analysis: age is not appropriate as time scale in Cox regression model

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Yangyang Liu ◽  
Jingjing Zhang ◽  
Toshiharu Mitsuhashi ◽  
Toshihiko Matsuo ◽  
Takashi Yorifuji ◽  
...  
Keyword(s):  
Regression Model ◽  
Time Scale ◽  
Cox Regression ◽  
Cox Model ◽  
Survival Function ◽  
Likelihood Estimation ◽  
Continuous Variable ◽  
Study Time ◽  
Right Censoring ◽  
Cox Regression Model

Abstract Background Many previous methodological studies suggested to use age as time scale in Cox regression model, and some statistical analyses directly applied this conclusion. In the present study, we explain why age is not a more appropriate time scale compared to the time-on-study time scale. Methods We address this argument based on five aspects: Cox regression model, conditional likelihood estimation, dataset of left-truncation or right-censoring, algorithms and software for Cox model, and inferring survival function. Furthermore, logical and algorithmic errors arise in the procedure of parameter inference with age time scale, and that certain evaluation indicators proposed by previous studies are inappropriate. Results The function of time scale is mainly a sampling method for maximum likelihood estimation to infer coefficient of Cox regression model, and the method defined by the age time scale is incorrect in logics and algorithms. Furthermore, age as time scale creates new problems, such as the omission of covariates, loss of information as a continuous variable, increase in dropout, and inability to obtain the survival function. Conclusions For the Cox regression model, the classic time-on-study time scale is more appropriate compared to age as time scale. Key messages It is an important discussion because using age as time scale was first proposed decades ago, meaning that lots of turnovers in researchers, newbies tend to accept the assumptions of their predecessors, but the suitability has never been rigorously verified.

scholarly journals A Study on the Amplitude Comparison Monopulse Algorithm

2020 ◽  
Vol 10 (11) ◽  
pp. 3966
Author(s):  
Minjeong Kim ◽  
Daseon Hong ◽  
Sungsu Park
Keyword(s):  
Monte Carlo ◽  
Numerical Simulations ◽  
Least Squares ◽  
Estimation Method ◽  
Prediction Equation ◽  
Least Squares Estimation ◽  
Estimation Accuracy ◽  
Prediction Equations ◽  
Special Case ◽  
Rms Errors

This paper presents two amplitude comparison monopulse algorithms and their covariance prediction equation. The proposed algorithms are based on the iterated least-squares estimation method and include the conventional monopulse algorithm as a special case. The proposed covariance equation is simple but predicts RMS errors very accurately. This equation quantitatively states estimation accuracy in terms of major parameters of amplitude comparison monopulse radar, and is also applicable to the conventional monopulse algorithm. The proposed algorithms and covariance prediction equations are validated by the numerical simulations with 100,000 Monte Carlo runs.

scholarly journals Modeling Claim Frequency in Indonesia Auto Insurance Using Generalized Poisson-Lindley Linear Model

2020 ◽  
Vol 16 (3) ◽  
pp. 428
Author(s):  
Mardianto Karim ◽  
Aceng Komarudin Mutaqin
Keyword(s):  
Linear Model ◽  
Linear Models ◽  
Motor Vehicle ◽  
Estimation Method ◽  
Secondary Data ◽  
Likelihood Estimation ◽  
Linear Modeling ◽  
Auto Insurance ◽  
Generalized Poisson ◽  
Claim Frequency

This paper will discuss the modeling of claim frequency from Indonesian auto insurance using the generalized Poisson-Lindley linear model. This modeling method assumes that the data of claim frequency are from populations that follow generalized Poisson-Lindley distribution. Generalized Poisson-Lindley linear model is an alternative to modeling count data that contains overdispersion. The parameters in the generalized Poisson-Lindley linear model can be estimated using the maximum likelihood estimation method through Newton Raphson's iteration numerical method. The data are the secondary data took from XYZ Company for the 2013 policy which is overdispersed. The data contains policyholder partial loss claims for comprehensive motor vehicle insurance products. From the research conducted it was concluded that the data is suitable to be modeled with generalized Poisson-Lindley linear models and produce better models than ordinary Poisson linear modeling because of produced the smaller AIC value. Of the 3 predictor variables that are modeled on the frequency of claims, 2 variables influenced they are the use variable and vehicle brand variable.

Institutional Quality and Trade Flow: Empirical Evidence from Malaysia and Other OIC Member Countries in Africa

2021 ◽  
pp. 097508782098717
Author(s):  
Hammed Agboola Yusuf ◽  
Luqman Olanrewaju Afolabi ◽  
Waliu Olawale Shittu ◽  
Kafilah Lola Gold ◽  
Murtala Muhammad
Keyword(s):  
Economic Growth ◽  
Bilateral Trade ◽  
Trade Flow ◽  
Estimation Method ◽  
Institutional Quality ◽  
Likelihood Estimation ◽  
Political Stability ◽  
Bilateral Trade Flow ◽  
World Governance Indicators ◽  
The Impact

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.

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

METRON ◽  
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.

scholarly journals Clinical significance of Q waves in ischemic cardiomyopathy

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
E Rodenas Alesina ◽  
P Jordan ◽  
L Herrador ◽  
C Espinet-Coll ◽  
N Pizzi ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Heart Failure ◽  
Primary Endpoint ◽  
Ischemic Cardiomyopathy ◽  
Cox Regression ◽  
Cox Model ◽  
Cardiovascular Death ◽  
P Value ◽  
Heart Failure Hospitalization ◽  
Total Cohort

Abstract Funding Acknowledgements Type of funding sources: Public hospital(s). Main funding source(s): CIBER-CV AIMS The scintigraphic translation of Q waves in patients with ischemic cardiomyopathy and LVEF < 40% has not yet been assessed. The aim of this study was to explore the relationship between Q waves and necrotic tissue and to analyze their impact in prognosis. METHODS AND RESULTS A retrospective study enrolling 487 consecutive patients (67,0 [57,4 – 75,4] years), with ischemic cardiomyopathy, LVEF <40% and narrow QRS who underwent stress-rest SPECT was conducted. Patients with Q waves (320 patients [65,7%]) had less comorbidity and ischemia, but more necrosis. Q waves correlated poorly with lack of viability (AUC = 0,63) and were independently associated with the subendocardial extent of the necrosis. After a follow-up of 5,07 years, the primary outcome (cardiovascular death, heart failure hospitalization or myocardial infarction) occurred in 192 (39,4%) patients, without differences between groups in multivariate analysis. After accounting for non-cardiovascular death as a competitive risk, the interaction between >10% of ischemia and revascularization remained in Cox model both in the total cohort (aHR= 0,46 [0,24 – 0,86]), and in patients with Q waves (aHR = 0,27 [0,11–0,69]). CONCLUSION Patients with ischemic cardiomyopathy with Q waves have larger subendocardial scarring and more transmural necrosis, although correlation between Q waves and transmural scarring is poor. Revascularization if >10% ischemia is present is associated with a better prognosis. Ischemia burden should be assessed and accordingly treated in these patients, and no differences in management should be made in the presence of Q waves. Table 1. Cox proportional hazards model Total cohort (N = 471) Patients with Q waves (N = 315) aHR p-value 95% CI aHR p-value 95% CI Age (per year) 1,02 0,007 1,01 - 1,04 n.s. Diabetes mellitus 1,35 0,047 1,00 - 1,81 1,54 0,016 1,09 - 2,20 eGFR < 60 ml/min 1,59 0,005 1,15 - 2,21 1,96 <0,001 1,36 - 2,82 Previous HF hospitalization 1,71 0,002 1,23 - 2,38 1,76 0,007 1,17 - 2,64 Previous PCI 1,32 0,069 0,98 - 1,78 n.s. Previous CABG n.s. 1,77 0,009 1,15 - 2,72 Angina or dyspnea 1,68 0,001 1,24 - 2,28 1,71 0,004 1,19 - 2,46 Indexed TDV (per quartile) 1,16 0,047 1,02 - 1,33 n.s. Revascularization*ischemia > 10% 0,46 0,015 0,24 - 0,86 0,27 0,006 0,11 - 0,69 Cox regression for the primary endpoint (cardiovascular death, heart failure hospitalization or myocardial infarction), accounting for non-cardiovascular death as a competitive risk. Abstract Figure. Survival for the primary endpoint

SiFi

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.

scholarly journals A New Inverted Topp-Leone Distribution: Applications to the COVID-19 Mortality Rate in Two Different Countries

Axioms ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 25 ◽  
Author(s):  
Ehab Almetwally ◽  
Randa Alharbi ◽  
Dalia Alnagar ◽  
Eslam Hafez
Keyword(s):  
Statistical Model ◽  
Least Squares ◽  
Weighted Least Squares ◽  
Likelihood Estimation ◽  
Linear Representation ◽  
Rate Function ◽  
Estimation Methods ◽  
Unknown Parameters ◽  
Least Squares Estimators ◽  
New Distribution

This paper aims to find a statistical model for the COVID-19 spread in the United Kingdom and Canada. We used an efficient and superior model for fitting the COVID 19 mortality rates in these countries by specifying an optimal statistical model. A new lifetime distribution with two-parameter is introduced by a combination of inverted Topp-Leone distribution and modified Kies family to produce the modified Kies inverted Topp-Leone (MKITL) distribution, which covers a lot of application that both the traditional inverted Topp-Leone and the modified Kies provide poor fitting for them. This new distribution has many valuable properties as simple linear representation, hazard rate function, and moment function. We made several methods of estimations as maximum likelihood estimation, least squares estimators, weighted least-squares estimators, maximum product spacing, Crame´r-von Mises estimators, and Anderson-Darling estimators methods are applied to estimate the unknown parameters of MKITL distribution. A numerical result of the Monte Carlo simulation is obtained to assess the use of estimation methods. also, we applied different data sets to the new distribution to assess its performance in modeling data.

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