检索结果-内蒙古大学图书馆

Behavior of R-estimators under measurement errors

BERNOULLI 2016年第2期22卷 1093-1112页

作者： Jureckova, Jana Koul, Hira L. Navratil, Radim Picek, Jan Charles Univ Prague Fac Math & Phys Sokolovska 83 CZ-18675 Prague 8 Czech Republic Michigan State Univ Stat & Probabil A435 Wells Hall E Lansing MI 48824 USA Masaryk Univ Dept Math & Stat Kotlarska 2 CS-61137 Brno Czech Republic Tech Univ Appl Math Voronezska 13 Liberec Czech Republic

As was shown recently, the measurement errors in regressors affect only the power of the rank test, but not its critical region. Noting that, we study the effect of measurement errors on R-estimators in linear model. It is demonstrated that while an R-estimator admits a local asymptotic bias, its bias surprisingly depends only on the precision of measurements and does neither depend on the chosen rank test score-generating function nor on the regression model error distribution. The R-estimators are numerically illustrated and compared with the LSE and L-1 estimators in this situation.

关键词： contiguity linear rank statistic linear regression model local asymptotic bias measurement error R-estimate

来源：评论

学校读者我要写书评

暂无评论

Trend and pattern classification of surface air temperature change in the Arctic region

引用

ATMOSPHERIC SCIENCE LETTERS 2016年第7期17卷 378-383页

作者： Wanishsakpong, Wandee McNeil, Nittaya Notodiputro, Khairil A. Prince Songkla Univ Fac Sci & Technol Dept Math & Comp Sci Pattani Thailand Commiss Higher Educ Ctr Excellence Math Bangkok Thailand Bogor Agr Univ Fac Math & Sci Dept Stat Bogor Indonesia

Monthly seasonally adjusted temperatures above latitude 45 degrees N were investigated from January 1973 to November 2013. The study area was divided into 69 sub-regions of similar size each in the shape of an igloo brick. The data were filtered with a second-order autoregressive process to remove autocorrelation. Two sub-regions did not have sufficient data due to substantial numbers of missing values. Factor analysis was then applied to the remaining 67 sub-regions and was used to classify regions with similar temperature changes. As a result, 63 sub-regions could be classified based on 12 factors but 4 sub-regions could not be grouped due to uniqueness. The temperatures for each group of sub-regions were found to increase during 1973-2013. The largest temperature increases of 0.19 degrees C/decade were found in northern and southern Siberia and part of the Arctic Ocean. In northern Canada, Alaska, the northern Pacific Ocean and eastern Siberia the temperatures increased by at least 0.16 degrees C/decade. In Iceland, Norway, Sweden and part of the Pacific and Arctic Oceans the temperature increased by around 0.15 degrees C/decade. In northeastern Canada, Greenland and its surrounding Atlantic Ocean and the Arctic Ocean the temperature increased by about 0.15 degrees C/decade.

关键词： Arctic climate change Time series analysis autocorrelation linear regression model factor analysis

来源：评论

学校读者我要写书评

暂无评论

Estimation of inverse autocovariance matrices for long memory processes

引用

BERNOULLI 2016年第3期22卷 1301-1330页

作者： Ing, Ching-Kang Chiou, Hai-Tang Guo, Meihui Acad Sinica Inst Stat Sci Taipei 11529 Taiwan Natl Sun Yat Sen Univ Dept Appl Math Kaohsiung 80424 Taiwan

This work aims at estimating inverse autocovariance matrices of long memory processes admitting a linear representation. A modified Cholesky decomposition is used in conjunction with an increasing order autoregressive model to achieve this goal. The spectral norm consistency of the proposed estimate is established. We then extend this result to linear regression models with long-memory time series errors. In particular, we show that when the objective is to consistently estimate the inverse autocovariance matrix of the error process, the same approach still works well if the estimated (by least squares) errors are used in place of the unobservable ones. Applications of this result to estimating unknown parameters in the aforementioned regression model are also given. Finally, a simulation study is performed to illustrate our theoretical findings.

关键词： inverse autocovariance matrix linear regression model long memory process modified Cholesky decomposition

来源：评论

学校读者我要写书评

暂无评论

Retrieval of Soil Dispersion Using Hyperspectral Remote Sensing

引用

JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING 2016年第4期44卷 563-572页

作者： Chen, Jia-ge Chen, Jun Wang, Qin-jun Zhang, Yue Ding, Hai-feng Huang, Zhang Beijing Normal Univ Beijing Peoples R China Natl Geomat Ctr China Beijing Peoples R China Chinese Acad Sci Inst Remote Sensing & Digital Earth Beijing Peoples R China

The aim of this study was to study the main determinants of soil dispersion, such as Na+, pH, kaolinite, illite and montmorillonite clay content, by grey relational analysis. Multiple linear regression and partial least squares regression were applied to establish correlations between soil dispersion and its main determinants. Raw spectra (or raw reflectance;RR) of 50 soil samples was measured between 350 and 2500 nm. Continuum-removal (CR) spectral reflectance was calculated. Relationships of Na+, pH, kaolinite, illite and montmorillonite clay content with spectral reflectance were constructed to find sensitive spectral bands and the best spectral indices. Multiple stepwise regression was used to calculate five determinants from hyperspectral reflectance. models were evaluated by the determinant (R-2), root mean square error, and relative root mean square error. Sensitive wavelengths were chosen based on the highest positive and negative correlations between five determinants and RR or CR reflectance. Results indicated that with the highest R-2 (0.686), the multiple linear regression model was the best for the prediction of soil dispersion using spectral reflectance. According to R-2 values, CR reflectance was the best predictor of Na+ (0.725), pH (0.852), kaolinite (0.909), illite (0.923) and montmorillonite (0.876). In conclusion, the methods examined here offered quick and novel means of predicting soil dispersion using spectral reflectance data.

关键词： Hyperspectral linear regression model Partial least squares model Stepwise regression

来源：评论

学校读者我要写书评

暂无评论

modelling the influence of dimerisation sequence dissimilarities on the auxin signalling network

引用

BMC SYSTEMS BIOLOGY 2016年第1期10卷 1-17页

作者： Legrand, Jonathan Leger, Jean-Benoist Robin, Stephane Vernoux, Teva Guedon, Yann Univ Lyon UCBL Lab Reprod & Dev Plantes CNRSINRAENS Lyon F-69364 Lyon France CIRAD UMR AGAP F-34095 Montpellier France Inria Virtual Plants F-34095 Montpellier France AgroParisTech INRA Math & Informat Appl F-75231 Paris France

Background: Auxin is a major phytohormone involved in many developmental processes by controlling gene expression through a network of transcriptional regulators. In Arabidopsis thaliana, the auxin signalling network is made of 52 potentially interacting transcriptional regulators, activating or repressing gene expression. All the possible interactions were tested in two-way yeast-2-hybrid experiments. Our objective was to characterise this auxin signalling network and to quantify the influence of the dimerisation sequence dissimilarities on the interaction between transcriptional regulators. Results: We applied model-based graph clustering methods relying on connectivity profiles between transcriptional regulators. Incorporating dimerisation sequence dissimilarities as explanatory variables, we modelled their influence on the auxin network topology using mixture of linear models for random graphs. Our results provide evidence that the network can be simplified into four groups, three of them being closely related to biological groups. We found that these groups behave differently, depending on their dimerisation sequence dissimilarities, and that the two dimerisation sub-domains might play different roles. Conclusions: We propose here the first pipeline of statistical methods combining yeast-2-hybrid data and protein sequence dissimilarities for analysing protein-protein interactions. We unveil using this pipeline of analysis the transcriptional regulator interaction modes.

关键词： Arabidospsis thaliana Auxin signalling network Transcriptional regulation linear regression model Mixture model for random graphs Plant development Binary and valued-graph clustering

来源：评论

学校读者我要写书评

暂无评论

Uniform integrability of the OLS estimators, and the convergence of their moments

引用

TEST 2016年第4期25卷 775-784页

作者： Afendras, Georgios Markatou, Marianthi SUNY Buffalo Dept Biostat 811 Kimball Tower Buffalo NY 14214 USA SUNY Buffalo Jacobs Sch Med & Biomed Sci 811 Kimball Tower Buffalo NY 14214 USA SUNY Buffalo Dept Biostat 726 Kimball Tower Buffalo NY 14214 USA SUNY Buffalo Jacobs Sch Med & Biomed Sci 726 Kimball Tower Buffalo NY 14214 USA

The problem of convergence of moments of a sequence of random variables to the moments of its asymptotic distribution is important in many applications. These include the determination of the optimal training sample size in the cross-validation estimation of the generalization error of computer algorithms, and in the construction of graphical methods for studying dependence patterns between two biomarkers. In this paper, we prove the uniform integrability of the ordinary least squares estimators of a linear regression model, under suitable assumptions on the design matrix and the moments of the errors. Further, we prove the convergence of the moments of the estimators to the corresponding moments of their asymptotic distribution, and study the rate of the moment convergence. The canonical central limit theorem corresponds to the simplest linear regression model. We investigate the rate of the moment convergence in canonical central limit theorem proving a sharp improvement of von Bahr's (Ann Math Stat 36:808-818, 1965) theorem.

关键词： linear regression model Moment convergence Rate of convergence Uniform integrability

来源：评论

学校读者我要写书评

暂无评论

The Story of Naive Alice: Behavioral Analysis of Susceptible Internet Users 40

The Story of Naive Alice: Behavioral Analysis of Susceptible...

引用

40th Annual IEEE Computer Software and Applications Conference Symposium (COMPSAC) / Symposium on Software Engineering Technology and Applications (SETA)

作者： Khan, Rasib Hasan, Ragib Univ Alabama Birmingham Dept CIS SECRETLab Birmingham AL 35487 USA

ISBN: (纸本)9781467388450

The Internet has become an integral part of our everyday life. Unfortunately, not all of us are equally aware of the threats when we use online services. Naive users are generally less aware of security and privacy practices on the Internet and are susceptible to online predators. In this paper, we present a behavioral analysis of Internet users and their susceptibility to online malpractices. We have considered the dataset from the Global Internet User Survey for 10789 respondents to perform a security-oriented statistical analysis of correlated user behavior. We constructed logistic regression models to analyze the statistical predictability of susceptible and not-so-susceptible identity theft victims based on their behavior and knowledge of security and privacy practices. We posit that such a study can be used to assess the vulnerability of Internet users and can hence be used to leverage institutional and personal safety on the Internet by promoting online security education, threat awareness, and guided Internet-safe behavior.

关键词： Behavioral Analysis Naive Alice linear regression model Susceptible User User model

来源：评论

学校读者我要写书评

暂无评论

Estimation of an unobservable parameters in the type II constraints in singular linear regression model

引用

MATHEMATICA SLOVACA 2010年第5期60卷 739-749页

作者： Kubacek, Lubomir Palacky Univ Fac Sci Dept Math Anal & Applicat Math CZ-77900 Olomouc Czech Republic

In regular linear regression model with the type II constraints the unobservable parameters in the constraints can be estimated by the BLUE of the observable parameters. The BLUE respects the constraints. If the estimator of the observable parameters which is the BLUE in the model without constraints is used, then the estimator of the unobservable parameters is the same. A problem is whether this is valid in the case of a singular model.

关键词： linear regression model type II constraints BLUE

来源：评论

学校读者我要写书评

暂无评论

Automatic Evaluation of a Summary's Linguistic Quality 21st

引用

21st International Conference on Applications of Natural Language to Information Systems (NLDB)

作者： Ellouze, Samira Jaoua, Maher Belguith, Lamia Hadrich Univ Sfax ANLP Res Grp MIRACL Lab Sfax Tunisia

ISBN: (纸本)9783319417547;9783319417530

The Evaluation of a summary's linguistic quality is a difficult task because several linguistic aspects (e.g. grammaticality, coherence, etc.) must be verified to ensure the well formedness of a text's summary. In this paper, we report the result of combining "Adapted ROUGE" scores and linguistic quality features to assess linguistic quality. We build and evaluate models for predicting the manual linguistic quality score using linear regression. We construct models for evaluating the quality of each text summary (summary level evaluation) and of each summarizing system (system level evaluation). We assess the performance of a summarizing system using the quality of a set of summaries generated by the system. All models are evaluated using the Pearson correlation and the Root mean squared error.

关键词： Automatic summary evaluation Linguistic quality linear regression model Machine learning

来源：评论

学校读者我要写书评

暂无评论

An Impact of linear regression models for Improving the Software Quality with Estimated Cost 11

An Impact of Linear Regression Models for Improving the Soft...

引用

11th International Conference on Data Mining and Warehousing (ICDMW)

作者： Marandi, Arun Kumar Khan, Danish Ali Natl Inst Technol Dept Comp Applicat Jamshedpur 831014 Bihar India

Developing organizations are spends lots of money to finding the Errors and bugs. In this article, an application of defects removal effectiveness to improve the software quality and fault prone analysis, methods are finding the solution of parameters in linear regression models with cost estimating method. It describes the approach of quantitative quality management through defect removal effectiveness and statistical process control of cost analysis with historical project data. Software quality is going continuously monetary benefit to perform well management planning, and achieve a new height. In this methodology, Software quality model can make timely predictions of reliability indications;it's enabling to improve software development processes by target reducing the estimated cost for software products and improve the techniques for more effectively and efficiently. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://***/licenses/by-nc-nd/4.0/).

关键词： Cost estimation Defect injection Defect removal linear regression model Quality management

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：