Model Assisted Statistics and Applications最新文献

Limitations of the propensity scores approach: A simulation study 倾向分数法的局限性：模拟研究

Model Assisted Statistics and Applications Pub Date : 2024-06-11 DOI: 10.3233/mas-241505

Igor Mandel

引用次数: 0

Estimation of three-parameter Fréchet distribution for the number of days from drug administration to remission in small sample sizes 小样本中从服药到病情缓解的天数的三参数弗雷谢特分布估计

Model Assisted Statistics and Applications Pub Date : 2024-06-11 DOI: 10.3233/mas-231466

T. Ogura, C. Shiraishi

{"title":"Estimation of three-parameter Fréchet distribution for the number of days from drug administration to remission in small sample sizes","authors":"T. Ogura, C. Shiraishi","doi":"10.3233/mas-231466","DOIUrl":"https://doi.org/10.3233/mas-231466","url":null,"abstract":"In medical research, it is common to estimate parameters for each group and then evaluate the estimated parameters for each group without comparing the groups. However, researchers frequently want to determine whether the two distributions using the estimated parameters differ significantly between the two groups. For the Weibull distribution, the two-sample Kolmogorov-Smirnov test (two-sided) was used to examine whether the two distributions were significantly different between the two groups. Based on this, we developed a method to compare the two groups using a three-parameter Fréchet distribution. The number of days from drug administration to remission frequently followed a Fréchet distribution. It is appropriate to use a three-parameter Fréchet distribution with a location parameter because patients typically go into remission after several days of drug administration. We propose a minimum variance linear estimator with a hyperparameter (MVLE-H) method for estimating a three-parameter Fréchet distribution based on the MVLE-H method for estimating a three-parameter Weibull distribution. We verified the effectiveness of the MVLE-H method and the two-sample Kolmogorov-Smirnov test (two-sided) on the three-parameter Fréchet distribution using Monte Carlo simulations and numerical examples.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":"14 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141356084","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}

引用次数: 0

Parametric analysis and model selection for economic evaluation of survival data 用于生存数据经济评估的参数分析和模型选择

Model Assisted Statistics and Applications Pub Date : 2024-06-11 DOI: 10.3233/mas-241506

Szilárd Nemes

{"title":"Parametric analysis and model selection for economic evaluation of survival data","authors":"Szilárd Nemes","doi":"10.3233/mas-241506","DOIUrl":"https://doi.org/10.3233/mas-241506","url":null,"abstract":"Health technology assessments of interventions impacting survival often require extrapolating current data to gain a better understanding of the interventions’ long-term benefits. Both a comprehensive examination of the trial data up to the maximum follow-up period and the fitting of parametric models are required for extrapolation. It is standard practice to visually compare the parametric curves to the Kaplan-Meier survival estimate (or comparison of hazard estimates) and to assess the parametric models using likelihood-based information criteria. In place of these two steps, this work demonstrates how to minimize the squared distance of parametric estimators to the Kaplan-Meier estimate. This is in line with the selection of the model using Mean Squared Error, with the modification that the unknown true survival is replaced by the Kaplan-Meier estimate. We would assure the internal validity of the extrapolated model and its appropriate representation of the data by adhering to this procedure. We use both simulation and real-world data with a scenario where no model that properly fits the data could be found to illustrate how this process can aid in model selection.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":"85 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141357978","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}

引用次数: 0

Development of out-of-sample forecast formulae for the FIGARCH model 开发 FIGARCH 模型的样本外预测公式

Model Assisted Statistics and Applications Pub Date : 2024-06-11 DOI: 10.3233/mas-241510

Debopam Rakshit, R. Paul

{"title":"Development of out-of-sample forecast formulae for the FIGARCH model","authors":"Debopam Rakshit, R. Paul","doi":"10.3233/mas-241510","DOIUrl":"https://doi.org/10.3233/mas-241510","url":null,"abstract":"Volatility is a matter of concern for time series modeling. It provides valuable insights into the fluctuation and stability of concerning variables over time. Volatility patterns in historical data can provide valuable information for predicting future behaviour. Nonlinear time series models such as the autoregressive conditional heteroscedastic (ARCH) and the generalized version of the ARCH model, i.e. generalized ARCH (GARCH) models are popularly used for capturing the volatility of a time series. The realization of any time series may have significant statistical dependencies on its distant counterpart. This phenomenon is known as the long memory process. Long memory structure can also be present in volatility. Fractionally integrated volatility models such as the fractionally integrated GARCH (FIGARCH) model can be used to capture the long memory in volatility. In this paper, we derived the out-of-sample forecast formulae along with the forecast error variances for the AR (1) -FIGARCH (1, d, 1) model by recursive use of conditional expectations and conditional variances. For empirical illustration, the modal spot prices of onion for Delhi, Lasalgaon and Bengaluru markets, India and S&P 500 index (close) data are used.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":"84 20","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141359800","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}

引用次数: 0

Analysis of kidney infection data using correlated compound poisson frailty models 利用相关复合泊松虚弱模型分析肾脏感染数据

Model Assisted Statistics and Applications Pub Date : 2024-06-11 DOI: 10.3233/mas-231452

David D. Hanagal

引用次数: 0

INAR(1) process with Poisson-transmuted record type exponential innovations 具有泊松传递记录类型指数创新的 INAR(1) 过程

Model Assisted Statistics and Applications Pub Date : 2024-06-11 DOI: 10.3233/mas-231458

M. Irshad, Muhammed Ahammed, R. Maya, Christophe Chesneau

{"title":"INAR(1) process with Poisson-transmuted record type exponential innovations","authors":"M. Irshad, Muhammed Ahammed, R. Maya, Christophe Chesneau","doi":"10.3233/mas-231458","DOIUrl":"https://doi.org/10.3233/mas-231458","url":null,"abstract":"In their article, Erbayram and Akdoğan (Ricerche di Matematica, 2023) introduced the Poisson-transmuted record type exponential distribution by combining the Poisson and transmuted record type exponential distributions. This article presents a novel approach to modeling time series data using integer-valued time series with binomial thinning framework and the Poisson-transmuted record type exponential distribution as the innovation distribution. This model demonstrates remarkable proficiency in accurately representing over-dispersed integer-valued time series. Under this configuration, which is a flexible and highly dependable choice, the model accurately captures the underlying patterns present in the time series data. A comprehensive analysis of the statistical characteristics of the process is given. The conditional maximum likelihood and conditional least squares methods are employed to estimate the process parameters. The performance of the estimates is meticulously evaluated through extensive simulation studies. Finally, the proposed model is validated using real-time series data and compared against existing models to demonstrate its practical effectiveness.","PeriodicalId":35000,"journal":{"name":"Model Assisted Statistics and Applications","volume":"28 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141355710","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}

引用次数: 0

Parametric modeling of receiver operating characteristics curves 接收器工作特性曲线的参数建模

Model Assisted Statistics and Applications Pub Date : 2024-06-11 DOI: 10.3233/mas-231475

P.M. Shankar

引用次数: 0

An asymmetric V-shaped distribution 不对称的 V 形分布

Model Assisted Statistics and Applications Pub Date : 2024-03-14 DOI: 10.3233/mas-231441

Tai Vo-Van, Thao Nguyen-Trang, Ha Che-Ngoc

引用次数: 0

New results and regression model for the exponentiated odd log-logistic family with applications 指数奇数对数逻辑族的新结果和回归模型及其应用

Model Assisted Statistics and Applications Pub Date : 2024-03-14 DOI: 10.3233/mas-231450

Gabriela M. Rodrigues, Roberto Vila, E. M. Ortega, G. Cordeiro, Victor Serra

引用次数: 0

Impact of missing data and ICC on full information maximum-likelihood estimation in multilevel SEMs 缺失数据和 ICC 对多层次 SEM 中全信息最大似然估计的影响

Model Assisted Statistics and Applications Pub Date : 2024-03-14 DOI: 10.3233/mas-231444

Chunling Niu

引用次数: 0