Journal of data science : JDS最新文献_第10页

A HETEROSCEDASTIC METHOD FOR COMPARING REGRESSION LINES AT SPECIFIED DESIGN POINTS WHEN USING A ROBUST REGRESSION ESTIMATOR. 在使用稳健回归估计量时，在指定设计点比较回归线的异方差方法。

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/JDS.2013.11(2).1146

R. Wilcox

{"title":"A HETEROSCEDASTIC METHOD FOR COMPARING REGRESSION LINES AT SPECIFIED DESIGN POINTS WHEN USING A ROBUST REGRESSION ESTIMATOR.","authors":"R. Wilcox","doi":"10.6339/JDS.2013.11(2).1146","DOIUrl":"https://doi.org/10.6339/JDS.2013.11(2).1146","url":null,"abstract":"It is well known that the ordinary least squares (OLS) regression estimator is not robust. Many robust regression estimators have been proposed and inferential methods based on these estimators have been derived. However, for two independent groups, let θj (X) be some conditional measure of location for the jth group, given X, based on some robust regression estimator. An issue that has not been addressed is computing a 1 - α confidence interval for θ1(X) - θ2(X) in a manner that allows both within group and between group hetereoscedasticity. The paper reports the finite sample properties of a simple method for accomplishing this goal. Simulations indicate that, in terms of controlling the probability of a Type I error, the method performs very well for a wide range of situations, even with a relatively small sample size. In principle, any robust regression estimator can be used. The simulations are focused primarily on the Theil-Sen estimator, but some results using Yohai's MM-estimator, as well as the Koenker and Bassett quantile regression estimator, are noted. Data from the Well Elderly II study, dealing with measures of meaningful activity using the cortisol awakening response as a covariate, are used to illustrate that the choice between an extant method based on a nonparametric regression estimator, and the method suggested here, can make a practical difference.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":"73 1","pages":"281-291"},"PeriodicalIF":0.0,"publicationDate":"2021-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73846635","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: 14

Adapted Autoregressive Model and Volatility Model with Application 自适应自回归模型与波动率模型及其应用

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/JDS.2013.11(4).1165

Naisheng Wang, Yan Lu

引用次数: 1

A New Procedure of Clustering Based on Multivariate Outlier Detection 一种基于多变量异常值检测的聚类新方法

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/JDS.2013.11(1).1091

Grégory David, S. Jayakumar, B. Thomas

{"title":"A New Procedure of Clustering Based on Multivariate Outlier Detection","authors":"Grégory David, S. Jayakumar, B. Thomas","doi":"10.6339/JDS.2013.11(1).1091","DOIUrl":"https://doi.org/10.6339/JDS.2013.11(1).1091","url":null,"abstract":"Clustering is an extremely important task in a wide variety of ap- plication domains especially in management and social science research. In this paper, an iterative procedure of clustering method based on multivariate outlier detection was proposed by using the famous Mahalanobis distance. At rst, Mahalanobis distance should be calculated for the entire sample, then using T 2 -statistic x a UCL. Above the UCL are treated as outliers which are grouped as outlier cluster and repeat the same procedure for the remaining inliers, until the variance-covariance matrix for the variables in the last cluster achieved singularity. At each iteration, multivariate test of mean used to check the discrimination between the outlier clusters and the inliers. Moreover, multivariate control charts also used to graphically visual- izes the iterations and outlier clustering process. Finally multivariate test of means helps to rmly establish the cluster discrimination and validity. This paper employed this procedure for clustering 275 customers of a famous two- wheeler in India based on 19 dierent attributes of the two wheeler and its company. The result of the proposed technique conrms there exist 5 and 7 outlier clusters of customers in the entire sample at 5% and 1% signicance level respectively.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49148312","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: 22

An Inference Model for Online Media Users 网络媒体用户的推理模型

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/JDS.201301_11(1).0008

N. Nananukul

引用次数: 0

modelSampler: An R Tool for Variable Selection and Model Exploration in Linear Regression modelSampler:线性回归中变量选择和模型探索的R工具

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/JDS.2013.11(2).1133

T. Dey

引用次数: 2

Use of Serial Weight and Length Measurements in Children from Birth to Two Years of Age to Predict Obesity at Five Years of Age 使用从出生到两岁儿童的连续体重和长度测量来预测五岁时的肥胖

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/JDS.2013.11(3).1154

H. Haller, T. Dey, L. Gittner, S. Ludington-Hoe

{"title":"Use of Serial Weight and Length Measurements in Children from Birth to Two Years of Age to Predict Obesity at Five Years of Age","authors":"H. Haller, T. Dey, L. Gittner, S. Ludington-Hoe","doi":"10.6339/JDS.2013.11(3).1154","DOIUrl":"https://doi.org/10.6339/JDS.2013.11(3).1154","url":null,"abstract":"Childhood obesity is a major health concern. The associated health risks dramatically reduce lifespan and increase healthcare costs. The goal was to develop methodology to identify as early in life as possible whether or not a child would become obese at age five. This diagnostic tool would facilitate clinical monitoring to prevent and or minimize obesity. Obesity is measured by Body Mass Index (BMI), but an improved metric, the ratio of weight to height (or length) (WOH), is proposed from this research for detecting early obesity. Results of this research demonstrate that WOH performs better than BMI for early detection of obesity in individuals using a longitudinal decision analysis (LDA), which is essentially an individuals type control chart analysis about a trend line. Utilizing LDA, the odds of obesity of a child at age five is indicated before the second birthday with 95% sensitivity and 97% specificity. Further, obesity at age five is indicated with 75% specificity before two months and with 84% specificity before three months of age. These results warrant expanding this study to larger cohorts of normal, overweight, and obese children at age five from different healthcare facilities to test the applicability of this novel diagnostic tool.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48169099","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: 1

Bayesian Behavior Scoring Model 贝叶斯行为评分模型

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/JDS.2013.11(3).1145

Ling-Jing Kao, F. Lin, C. Yu

引用次数: 2

On Estimation of Rayleigh Scale Parameter under Doubly Type-II Censoring from Imprecise Data 非精确数据双ii型滤波下瑞利尺度参数的估计

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/JDS.2013.11(2).1144

Abbas Pak, G. Parham, M. Saraj

引用次数: 9

Modelling Progression of HIV/AIDS Disease Stages Using Semi-Markov Processes 用半马尔可夫过程模拟HIV/AIDS疾病阶段的进展

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/jds.201304_11(2).0004

A. Goshu, Zelalem G. Dessie

{"title":"Modelling Progression of HIV/AIDS Disease Stages Using Semi-Markov Processes","authors":"A. Goshu, Zelalem G. Dessie","doi":"10.6339/jds.201304_11(2).0004","DOIUrl":"https://doi.org/10.6339/jds.201304_11(2).0004","url":null,"abstract":"The aim of this study is to model the progression of HIV/AIDS disease of an individual patient under ART follow-up using semi-Markov processes. Recorded hospital data were obtained for a cohort of 710 patients at Felege-Hiwot referral hospital, Ethiopia, who have been under ART followup from June 2005 to August 2009. States of the Markov process are defined by the seriousness of the sickness based on the CD4 counts in cells/microliter. The five states considered are: state one (CD4 count > 500); state two (350 < CD4 count ≤ 500); state three (200 < CD4 count ≤ 350); state four (CD4 count ≤ 200); and state five (Death). The first four states are named as good or alive states. The findings obtained from the current study are as follows: within the good states, the transition probability from a given state to the next worse state increases with time, gets optimum at a time and then decreases with increasing time. This means that there is some period of time when such probability is highest for a patient to transit to a worse state of the disease. Moreover, the probability of dying decreases with increasing CD4 counts over time. For an HIV/AIDS patient in a specific state of the disease, the probability of being in same state decreases over time. Within the good states, the results show that probability of being in a better state is non-zero, but less than the probability of being in worse state. At any time of the process, there is more likely to be in worse state than to be in better one. The conditional probability of staying in same state until a given number of month decreases with increasing time. The reliability analysis also revealed that the survival probabilities are all declining over time. This implies that patient conditions should be improved with ART to improve the survival probability.","PeriodicalId":73699,"journal":{"name":"Journal of data science : JDS","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46846149","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: 22

Two-Level Factorial Design with Circular Response: Model and Analysis 具有圆形响应的两级因子设计：模型与分析

Journal of data science : JDS Pub Date : 2021-07-30 DOI: 10.6339/jds.201307_11(3).0003

A. Zahran

引用次数: 2