Pub Date : 2022-01-01DOI: 10.4236/ojmsi.2022.102012
L. Gustafsson, E. Gustafsson, M. Gustafsson
It is vital that a well-defined conceptual model can be realized by a macro-model (e.g., a Continuous System Simulation (CSS) model) or a micro-model (e.g., an Agent-Based model or Discrete Event Simulation model) and still produce mutually consistent results. The Full Potential CSS concept provides the rules so that the results from macro-modelling become fully consistent with those from micro-modelling. This paper focuses on the simulation language StochSD (Stochastic System Dynamics), which is an extension of classical Continuous System Simulation that implements the Full Potential CSS concept. Thus, in addition to modelling and simulating continuous flows between compartments represented by “real” numbers, it can also handle transitions of discrete entities by integer numbers, enabling combined models to be constructed in a straight-forward way. However, transition events of discrete entities (e.g., arrivals, accidents, deaths) usually happen irregularly over time, so stochasticity often plays a crucial role in their modelling. Therefore, StochSD contains powerful random functions to model uncertainties of different kinds, together with devices to collect statistics during a simulation or from multiple replications of the same stochastic model. Also, tools for sensitivity analysis, optimisation and statistical analysis are included. In particular, StochSD includes features for stochastic modelling, post-analysis of multiple simulations, and presentation of the results in statistical form. In addition to making StochSD a Full Potential CSS language, sive material for a course in Modelling and Simulation in form of PowerPoint lectures and laboratory exercises.
重要的是，定义良好的概念模型可以通过宏观模型(例如，连续系统仿真(CSS)模型)或微观模型(例如，基于代理的模型或离散事件仿真模型)实现，并且仍然产生相互一致的结果。全潜能CSS概念提供了规则，使宏观建模的结果与微观建模的结果完全一致。本文重点研究了随机系统动力学(Stochastic System Dynamics，随机系统动力学)仿真语言，它是经典连续系统仿真的扩展，实现了全潜能CSS概念。因此，除了建模和模拟用“实数”表示的间隔之间的连续流外，它还可以用整数处理离散实体的转换，从而可以直接构建组合模型。然而，离散实体的过渡事件(例如，到达，事故，死亡)通常随时间不规则地发生，因此随机性通常在其建模中起着至关重要的作用。因此，随机sd包含强大的随机函数来模拟不同类型的不确定性，以及在模拟期间或从同一随机模型的多个复制中收集统计数据的设备。此外，工具的敏感性分析，优化和统计分析包括在内。特别是，随机sd包括随机建模、多次模拟的后期分析和以统计形式表示结果的特征。除了使stacsd成为一个充分发挥潜力的CSS语言之外，它还以PowerPoint讲座和实验练习的形式为建模和仿真课程提供了大量材料。
{"title":"StochSD: A Full Potential CSS Language for Dynamic and Stochastic Modelling, Simulation and Statistical Analysis","authors":"L. Gustafsson, E. Gustafsson, M. Gustafsson","doi":"10.4236/ojmsi.2022.102012","DOIUrl":"https://doi.org/10.4236/ojmsi.2022.102012","url":null,"abstract":"It is vital that a well-defined conceptual model can be realized by a macro-model (e.g., a Continuous System Simulation (CSS) model) or a micro-model (e.g., an Agent-Based model or Discrete Event Simulation model) and still produce mutually consistent results. The Full Potential CSS concept provides the rules so that the results from macro-modelling become fully consistent with those from micro-modelling. This paper focuses on the simulation language StochSD (Stochastic System Dynamics), which is an extension of classical Continuous System Simulation that implements the Full Potential CSS concept. Thus, in addition to modelling and simulating continuous flows between compartments represented by “real” numbers, it can also handle transitions of discrete entities by integer numbers, enabling combined models to be constructed in a straight-forward way. However, transition events of discrete entities (e.g., arrivals, accidents, deaths) usually happen irregularly over time, so stochasticity often plays a crucial role in their modelling. Therefore, StochSD contains powerful random functions to model uncertainties of different kinds, together with devices to collect statistics during a simulation or from multiple replications of the same stochastic model. Also, tools for sensitivity analysis, optimisation and statistical analysis are included. In particular, StochSD includes features for stochastic modelling, post-analysis of multiple simulations, and presentation of the results in statistical form. In addition to making StochSD a Full Potential CSS language, sive material for a course in Modelling and Simulation in form of PowerPoint lectures and laboratory exercises.","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70368651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.4236/ojmsi.2022.103016
Rongrong Hu, Xumin Zhou, Yiping Yu
{"title":"Application Research on Real-Time Interactive Simulation System of Container Yard Based on Unity3D","authors":"Rongrong Hu, Xumin Zhou, Yiping Yu","doi":"10.4236/ojmsi.2022.103016","DOIUrl":"https://doi.org/10.4236/ojmsi.2022.103016","url":null,"abstract":"","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70368818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.4236/ojmsi.2022.101002
Sanae Chakir, A. Bekraoui, H. Majdoubi, A. Senhaji, M. Mouqallid
{"title":"Numerical Simulation and Measurement of Air Temperature and Relative Humidity in an Olive Cuttings Tunnel Greenhouse","authors":"Sanae Chakir, A. Bekraoui, H. Majdoubi, A. Senhaji, M. Mouqallid","doi":"10.4236/ojmsi.2022.101002","DOIUrl":"https://doi.org/10.4236/ojmsi.2022.101002","url":null,"abstract":"","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70368132","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.4236/ojmsi.2022.103014
Z. M. Alaofi, T. El-Danaf, Adel R. Hadhoud, S. Dragomir
{"title":"Computational Analysis for Solving the Linear Space-Fractional Telegraph Equation","authors":"Z. M. Alaofi, T. El-Danaf, Adel R. Hadhoud, S. Dragomir","doi":"10.4236/ojmsi.2022.103014","DOIUrl":"https://doi.org/10.4236/ojmsi.2022.103014","url":null,"abstract":"","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70368662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01DOI: 10.4236/ojmsi.2022.104022
Sadiah M. A. Aljeddani
This paper discussed Bayesian variable selection methods for models from split-plot mixture designs using samples from Metropolis-Hastings within the Gibbs sampling algorithm. Bayesian variable selection is easy to implement due to the improvement in computing via MCMC sampling. We described the Bayesian methodology by introducing the Bayesian framework, and explaining Markov Chain Monte Carlo (MCMC) sampling. The Metropolis-Hastings within Gibbs sampling was used to draw dependent samples from the full conditional distributions which were explained. In mixture experiments with process variables, the response depends not only on the proportions of the mixture components but also on the effects of the process variables. In many such mixture-process variable experiments, constraints such as time or cost prohibit the selection of treatments completely at random. In these situations, restrictions on the randomisation force the level combinations of one group of factors to be fixed and the combinations of the other group of factors are run. Then a new level of the first-factor group is set and combinations of the other factors are run. We discussed the computational algorithm for the Stochastic Search Variable Selection (SSVS) in linear mixed models. We extended the computational algorithm of SSVS to fit models from split-plot mixture design by introducing the algorithm of the Stochastic Search Variable Selection for Split-plot Design (SSVS-SPD). The motivation of this extension is that we have two different levels of the experimental units, one for the whole plots and the other for subplots in the split-plot mixture design.
本文讨论了分离式混合设计模型的贝叶斯变量选择方法，使用吉布斯抽样算法中的Metropolis-Hastings样本。由于通过MCMC采样改进了计算能力，贝叶斯变量选择易于实现。我们通过介绍贝叶斯框架来描述贝叶斯方法，并解释了马尔可夫链蒙特卡罗(MCMC)抽样。采用Metropolis-Hastings within Gibbs抽样法从已解释的完全条件分布中抽取相关样本。在有工艺变量的混合实验中，响应不仅取决于混合组分的比例，还取决于工艺变量的影响。在许多这样的混合工艺变量实验中，时间或成本等限制因素禁止完全随机选择处理方法。在这种情况下，随机性的限制迫使一组因素的关卡组合被固定，而另一组因素的组合被运行。然后设置第一个因素组的新水平，并运行其他因素的组合。讨论了线性混合模型中随机搜索变量选择的计算算法。通过引入split-plot design随机搜索变量选择算法(SSVS- spd)，将SSVS的计算算法扩展到适合分块混合设计模型。这个扩展的动机是我们有两个不同级别的实验单元，一个用于整个地块，另一个用于分裂地块混合设计中的子地块。
{"title":"Bayesian Variable Selection for Mixture Process Variable Design Experiment","authors":"Sadiah M. A. Aljeddani","doi":"10.4236/ojmsi.2022.104022","DOIUrl":"https://doi.org/10.4236/ojmsi.2022.104022","url":null,"abstract":"This paper discussed Bayesian variable selection methods for models from split-plot mixture designs using samples from Metropolis-Hastings within the Gibbs sampling algorithm. Bayesian variable selection is easy to implement due to the improvement in computing via MCMC sampling. We described the Bayesian methodology by introducing the Bayesian framework, and explaining Markov Chain Monte Carlo (MCMC) sampling. The Metropolis-Hastings within Gibbs sampling was used to draw dependent samples from the full conditional distributions which were explained. In mixture experiments with process variables, the response depends not only on the proportions of the mixture components but also on the effects of the process variables. In many such mixture-process variable experiments, constraints such as time or cost prohibit the selection of treatments completely at random. In these situations, restrictions on the randomisation force the level combinations of one group of factors to be fixed and the combinations of the other group of factors are run. Then a new level of the first-factor group is set and combinations of the other factors are run. We discussed the computational algorithm for the Stochastic Search Variable Selection (SSVS) in linear mixed models. We extended the computational algorithm of SSVS to fit models from split-plot mixture design by introducing the algorithm of the Stochastic Search Variable Selection for Split-plot Design (SSVS-SPD). The motivation of this extension is that we have two different levels of the experimental units, one for the whole plots and the other for subplots in the split-plot mixture design.","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70369038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-27DOI: 10.4236/ojmsi.2021.94024
D. C. Bartholomew, U. C. Orumie, C. P. Obite, Blessing Iheoma Duru, F. C. Akanno
Several authors have used different classical statistical models to fit the Nigerian Bonny Light crude oil price but the application of machine learning models and Fuzzy Time Series model on the crude oil price has been grossly understudied. Therefore, in this study, a classical statistical model—Autoregressive Integrated Moving Average (ARIMA), two machine learning models—Artificial Neural Network (ANN) and Random Forest (RF) and Fuzzy Time Series (FTS) Model were compared in modeling the Nigerian Bonny Light crude oil price data for the periods from January, 2006 to December, 2020. The monthly secondary data were collected from the Nigerian National Petroleum Corporation (NNPC) and Reuters website and divided into train (70%) and test (30%) sets. The train set was used in building the models and the models were validated using the test set. The performance measures used for the comparison include: The modified Diebold-Mariano test, the Root Mean Square Error (RMSE), the Mean Absolute Percentage Error (MAPE) and Nash-Sutcliffe Efficiency (NSE) values. Based on the performance measures, ANN (4, 1, 1) and RF performed better than ARIMA (1, 1, 0) model but FTS model using Chen’s algorithm outperformed every other model. The results recommend the use of FTS model for forecasting future values of the Nigerian Bonny Light Crude oil. However, a hybrid model of ARIMA-ANN or ARIMA-RF should be built and compared with Chen’s algorithm FTS model for the same data set to further verify the power of FTS model using Chen’s algorithm.
{"title":"Modeling the Nigerian Bonny Light Crude Oil Price: The Power of Fuzzy Time Series","authors":"D. C. Bartholomew, U. C. Orumie, C. P. Obite, Blessing Iheoma Duru, F. C. Akanno","doi":"10.4236/ojmsi.2021.94024","DOIUrl":"https://doi.org/10.4236/ojmsi.2021.94024","url":null,"abstract":"Several authors have used different classical statistical models to fit \u0000the Nigerian Bonny Light crude oil price but the application of machine \u0000learning models and Fuzzy Time Series model on the crude oil price has been \u0000grossly understudied. Therefore, in this study, a classical statistical model—Autoregressive Integrated Moving Average (ARIMA), \u0000two machine learning models—Artificial \u0000Neural Network (ANN) and Random Forest (RF) and Fuzzy Time Series (FTS) Model \u0000were compared in modeling the Nigerian Bonny Light crude oil price data for the \u0000periods from January, 2006 to December, 2020. The monthly secondary data were \u0000collected from the Nigerian National Petroleum Corporation (NNPC) and Reuters \u0000website and divided into train (70%) and test (30%) sets. The train set was \u0000used in building the models and the models were validated using the test set. The \u0000performance measures used for the comparison include: The modified \u0000Diebold-Mariano test, the Root Mean Square Error (RMSE), the Mean Absolute \u0000Percentage Error (MAPE) and Nash-Sutcliffe Efficiency (NSE) values. Based on \u0000the performance measures, ANN (4, 1, 1) and RF performed better than ARIMA (1, 1, \u00000) model but FTS model using Chen’s algorithm outperformed every other model. \u0000The results recommend the use of FTS model for forecasting future values of the \u0000Nigerian Bonny Light Crude oil. However, a hybrid model of ARIMA-ANN or \u0000ARIMA-RF should be built and compared with Chen’s algorithm FTS model for the \u0000same data set to further verify the power of FTS model using Chen’s algorithm.","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44496729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-27DOI: 10.4236/ojmsi.2021.94022
A. Sylla, N’Guessan Armel Ignace, T. Siaka, J. Vilcot
The aim of this work is to analyze the influence of the interfacial MoSe2 layer on the performance of a /n-ZnO/i-ZnO/n-Zn(O,S)/p-CIGS/p+-MoSe2/Mo/SLG solar cell. In this investigation, the numerical simulation software AFORS-HET is used to calculate the electrical characteristics of the cell with and without this MoSe2 layer. Different reported experimental works have highlighted the presence of a thin-film MoSe2 layer at the CIGS/Mo contact interface. Under a tunneling effect, this MoSe2 layer transforms the Schottky CIGS/Mo contact nature into a quasi-ohmic one. Owing to a heavily p-doping, the MoSe2 thin layer allows better transport of majority carrier, tunneling them from CIGS to Mo. Moreover, the bandgap of MoSe2 is wider than that of the CIGS absorbing layer, such that an electric field is generated close to the back surface. The presence of this electric field reduces carrier recombination at the interface. Under these conditions, we examined the performance of the cell with and without MoSe2 layer. When the thickness of the CIGS absorber is in the range from 3.5 μm down to 1.5 μm, the efficiency of the cell with a MoSe2 interfacial layer remains almost constant, about 24.6%, while that of the MoSe2-free solar cell decreases from 24.6% to 23.4%. Besides, a Schottky barrier height larger than 0.45 eV severely affects the fill factor and open circuit voltage of the solar cell with MoSe2 interface layer compared to the MoSe2-free solar cell.
{"title":"Theoretical Analysis of the Effect of the Interfacial MoSe2 Layer in CIGS-Based Solar Cells","authors":"A. Sylla, N’Guessan Armel Ignace, T. Siaka, J. Vilcot","doi":"10.4236/ojmsi.2021.94022","DOIUrl":"https://doi.org/10.4236/ojmsi.2021.94022","url":null,"abstract":"The aim of this work is to analyze the influence of the interfacial MoSe2 layer on the performance of a \u0000/n-ZnO/i-ZnO/n-Zn(O,S)/p-CIGS/p+-MoSe2/Mo/SLG solar cell. In this investigation, the numerical simulation software AFORS-HET is used to calculate the electrical \u0000characteristics of the cell with and without this MoSe2 layer. Different \u0000reported experimental works have highlighted the presence of a thin-film MoSe2 layer at the \u0000CIGS/Mo contact interface. Under a tunneling effect, this MoSe2 layer transforms \u0000the Schottky CIGS/Mo contact nature into a quasi-ohmic one. Owing to a heavily \u0000p-doping, the MoSe2 thin layer allows better transport of majority carrier, tunneling them from \u0000CIGS to Mo. Moreover, the bandgap of MoSe2 is wider than that of the CIGS absorbing layer, such that an electric field is \u0000generated close to the back surface. The presence of this electric field \u0000reduces carrier recombination at the interface. Under these conditions, we \u0000examined the performance of the cell with and without MoSe2 layer. When the \u0000thickness of the CIGS absorber is in the range from 3.5 μm down to 1.5 μm, the \u0000efficiency of the cell with a MoSe2 interfacial layer remains almost constant, about 24.6%, while that of the MoSe2-free \u0000solar cell decreases from 24.6% to 23.4%. Besides, a Schottky barrier height \u0000larger than 0.45 eV severely affects the fill factor and open circuit voltage \u0000of the solar cell with MoSe2 interface layer compared to the MoSe2-free solar cell.","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45299640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-27DOI: 10.4236/ojmsi.2021.94021
Ahmed T. Ramadan, A. Tolba, B. El-Desouky
In this paper, a new two-parameter distribution called generalized power Akshaya distribution extended from Akshaya distribution is introduced. This distribution is proposed to model lifetime data. Statistical properties like density, hazard, survival and moments are derived. Two parameters estimation is introduced using maximum likelihood and Bayesian techniques. Finally, an application of real data and a simulation study are introduced to illustrate the usefulness of the proposed distribution.
{"title":"Generalized Power Akshaya Distribution and Its Applications","authors":"Ahmed T. Ramadan, A. Tolba, B. El-Desouky","doi":"10.4236/ojmsi.2021.94021","DOIUrl":"https://doi.org/10.4236/ojmsi.2021.94021","url":null,"abstract":"In this paper, a new \u0000two-parameter distribution called generalized power Akshaya distribution extended from Akshaya distribution is introduced. This \u0000distribution is proposed to model lifetime data. Statistical properties like \u0000density, hazard, survival and moments are derived. Two parameters estimation is \u0000introduced using maximum likelihood and Bayesian techniques. Finally, an \u0000application of real data and a simulation study are introduced to illustrate \u0000the usefulness of the proposed distribution.","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44786304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-08-27DOI: 10.4236/ojmsi.2021.94023
M. M. Buzaridah, Dina A. Ramadan, B. El-Desouky
In this paper, a new method for adding parameters to a well-established distribution to obtain more flexible new families of distributions is applied to the inverse Lomax distribution (IFD). This method is known by the flexible reduced logarithmic-X family of distribution (FRL-X). The proposed distribution can be called a flexible reduced logarithmic-inverse Lomax distribution (FRL-IL). The statistical and reliability properties of the proposed models are studied including moments, order statistics, moment generating function, and quantile function. The estimation of the model parameters by maximum likelihood and the observed information matrix are also discussed. In order to assess the potential of the newly created distribution. The extended model is applied to real data and the results are given and compared to other models.
{"title":"Flexible Reduced Logarithmic-Inverse Lomax Distribution with Application for Bladder Cancer","authors":"M. M. Buzaridah, Dina A. Ramadan, B. El-Desouky","doi":"10.4236/ojmsi.2021.94023","DOIUrl":"https://doi.org/10.4236/ojmsi.2021.94023","url":null,"abstract":"In this paper, a new method for adding parameters to \u0000a well-established distribution to obtain more flexible new families of \u0000distributions is applied to the inverse Lomax distribution (IFD). This method \u0000is known by the flexible reduced logarithmic-X family of distribution (FRL-X). \u0000The proposed distribution can be called a flexible reduced logarithmic-inverse \u0000Lomax distribution (FRL-IL). The statistical and reliability properties of the \u0000proposed models are studied including moments, order statistics, moment generating \u0000function, and quantile function. The estimation of the model parameters by \u0000maximum likelihood and the observed information matrix are also discussed. In \u0000order to assess the potential of the newly created distribution. The extended \u0000model is applied to real data and the results are given and compared to other \u0000models.","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41830444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-05-21DOI: 10.4236/ojmsi.2021.93018
H. Lu, Cuiling Dong, Juling Zhou
In the applications of Tobit regression models we always encounter the data sets which contain too many variables that only a few of them contribute to the model. Therefore, it will waste much more samples to estimate the “non-effective” variables in the inference. In this paper, we use a sequential procedure for constructing the fixed size confidence set for the “effective” parameters to the model by using an adaptive shrinkage estimate such that the “effective” coefficients can be efficiently identified with the minimum sample size based on Tobit regression model. Fixed design is considered for numerical simulation.
{"title":"A Sequential Shrinkage Estimating Method for Tobit Regression Model","authors":"H. Lu, Cuiling Dong, Juling Zhou","doi":"10.4236/ojmsi.2021.93018","DOIUrl":"https://doi.org/10.4236/ojmsi.2021.93018","url":null,"abstract":"In the applications of Tobit regression models we always encounter the \u0000data sets which contain too many variables that only a few of them contribute \u0000to the model. Therefore, it will waste much more samples to estimate the “non-effective” \u0000variables in the inference. In this paper, we use a sequential procedure for \u0000constructing the fixed size confidence set for the “effective” parameters to \u0000the model by using an adaptive shrinkage estimate such that the “effective” \u0000coefficients can be efficiently identified with the minimum sample size based \u0000on Tobit regression model. Fixed design is considered for numerical simulation.","PeriodicalId":56990,"journal":{"name":"建模与仿真(英文)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41534031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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