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Factor analysis and linear regression model (LRM) of metal speciation and physico-chemical characters of groundwater samples

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ENVIRONMENTAL MONITORING AND ASSESSMENT 2008年第1-3期138卷 65-79页

作者： Kumaresan, M. Riyazuddin, P. Univ Madras Dept Analyt Chem Madras 600025 Tamil Nadu India

An approach is described for viewing the interrelationship between different variables and also tracing the sources of pollution of groundwater of north Chennai (India). The data set of 43 variables which include major ions, minor ions and trace metal speciation (Cu, Pb, Cd and Zn) collected during the pre-monsoon and post-monsoon seasons of the year 2000-2001, was subjected to R-mode factor analysis to comprehend the distribution pattern of the said variables. It was found that first factor measures salinity and hardness which explained 19.12% of the total variance (comprised of variables EC, TDS, Na+, K+, Ca2+, Mg2+, total hardness, Cl- and SO42-) during pre-monsoon, while it was 25.08% during post-monsoon. The second and third factors were attributed to speciation of zinc and copper ions during both pre-monsoon and post-monsoon. Although there were two more factors, loaded with speciation parameters of lead and cadmium, the variance of them were less than 10%. From this study it is seen that sea water intrusion, municipal solid waste disposal are the identified sources of component of pollution. The importance of metal ions is taking a secondary role and the anthropogenic origin-industrial activity, is the reason in the evaluation of pollution status as they come in the second, third, fourth and fifth factors. As the trace metal speciation was grouped in separate factors, linear regression model (LRM) with correlation analysis was applied to check its validity for prediction of speciation and to apply LRM for rapid monitoring of water pollution.

关键词： factor analysis groundwater linear regression model metal speciation physico-chemical characters

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Empirical likelihood ratio test for a change-point in linear regression model

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 2008年第16期37卷 2551-2563页

作者： Liu, Yukun Zou, Changliang Zhang, Runchu Nankai Univ LPMC Tianjin 300071 Peoples R China Nankai Univ Sch Math Sci Tianjin 300071 Peoples R China

A nonparametric method based on the empirical likelihood is proposed to detect the change-point in the coefficient of linear regression models. The empirical likelihood ratio test statistic is proved to have the same asymptotic null distribution as that with classical parametric likelihood. Under some mild conditions, the maximum empirical likelihood change-point estimator is also shown to be consistent. The simulation results show the sensitivity and robustness of the proposed approach. The method is applied to some real datasets to illustrate the effectiveness.

关键词： change-point empirical likelihood linear regression model maximum empirical likelihood estimator nonparametric robustness

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Asymptotics of prediction in functional linear regression with functional outputs

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BERNOULLI 2013年第5B期19卷 2627-2651页

作者： Crambes, Christophe Mas, Andre Univ Montpellier 2 Equipe Probabilites & Stat Inst Math & Modelisat Montpellier CNRSUMR 5149 F-34095 Montpellier 5 France

We study prediction in the functional linear model with functional outputs, Y = SX + epsilon, where the covariates X and Y belong to some functional space and S is a linear operator. We provide the asymptotic mean square prediction error for a random input with exact constants for our estimator which is based on the functional PCA of X. As a consequence we derive the optimal choice of the dimension k(n) of the projection space. The rates we obtain are optimal in minimax sense and generalize those found when the output is real. Our main results hold for class of inputs X(.) that may be either very irregular or very smooth. We also prove a central limit theorem for the predictor. We show that, due to the underlying inverse problem, the bare estimate cannot converge in distribution for the norm of the function space.

关键词： functional data functional output linear regression model optimality prediction mean square error weak convergence

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Asymptotic normality of Huber-Dutter estimators in a linear model with AR(1) processes

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JOURNAL OF STATISTICAL PLANNING AND INFERENCE 2013年第3期143卷 548-562页

作者： Hu, Hongchang Hubei Normal Univ Sch Math & Stat Huangshi 435002 Peoples R China

The paper studies a linear regression model with first order autoregressive (AR(1)) processes. The Huber-Dutter (HD) estimators of unknown parameters are given, and the asymptotic normality of the HD estimators is inv... 详细信息

关键词： linear regression model Huber-Dutter estimator Autoregressive processes Asymptotic normality

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Prediction of CIELab data and wash fastness of nylon 6,6 using artificial neural network and linear regression model

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FIBERS AND POLYMERS 2008年第2期9卷 217-224页

作者： Balci, Onur Ogulata, S. Noyan Sahin, Cenk Ogullata, R. Tugrul Cukurova Univ Dept Text Engn TR-01330 Adana Turkey Cukurova Univ Dept Ind Engn TR-01330 Adana Turkey

We tried to predict the CIELab data and wash fastness values of scoured nylon 6.6 knitted fabric dyed with 1:2 metal-complex acid dyes and aftertreated using three different methods named as syntan, syntan/cation and full backtan by artificial neural network (ANN) with Levenberg-Marquardt algorithm and regression models. Afterward, the predicting performance of these models was tested and compared with each other using unseen data sets. We were able to achieve to predict the all colorimetric data satisfactorily such as L*, a*, b*, C, h degrees and wash fastness performance using both models. The statistical findings indicated that the regression models provide more accurate prediction for all colour data with an average error of 1% contrast to previous study. In terms of prediction of fastness, artificial neural network is a bit more useful than regression models for prediction of staining value on the nylon part of adjacent multifiber.

关键词： CIELab wash fastness artificial neural network Levenberg-Marquardt algorithm linear regression model

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End of Discharge Time Prediction for Li-ion Battery

End of Discharge Time Prediction for Li-ion Battery

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International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering

作者： Zhou, Zhenwei Shi, Zhengyu Ai, Guo Lu, Yudong En, Yunfei China Elect Prod Reliabil & Environm Testing Res Sci & Technol Reliabil Phys & Applicat Elect Comp Guangzhou Guangdong Peoples R China

ISBN: (纸本)9781479910144

How to predict the end of discharge time for Li-ion battery is one of the most important problems in the field of battery health management. This paper proposes a linear regression model to describe the relationship between the end of discharge time and discharge cycle. Moreover, the model verification shows that the discharge cycle has significant effect on the end of discharge time and that the proposed model has good fitness in fitting Li-ion discharge data. This paper also presents the end of discharge time predictions for Li-ion battery based on the linear regression model.

关键词： Li-ion battery end of discharge time prediction linear regression model hypothesis testing

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A Proposal for a Discriminant Analysis Based on the Results of a Preliminary Fuzzy Clustering

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13th International Conference on Computational Science and Its Applications (ICCSA)

作者： Campobasso, Francesco Fanizzi, Annarita Univ Bari Dept Econ & Math I-70100 Bari Italy

ISBN: (纸本)9783642396496

The common classification techniques are designed for a rigid (even if probabilistic) allocation of each unit into one of several groups. Nevertheless the dissimilarity among combined units often leads to consider the opportunity of assigning each of them to more than a single group with different degrees of membership. The same logic can be applied in attributing a new observation to previously identified fuzzy groups. This paper precisely presents a proposal for a discriminant analysis, structured by regressing the degrees of membership to every groups of each unit on the same variables used in a preliminary clustering. Such a proposal, initially conceived to assign new customers to defined groups for Customer Relationship Management (CRM) purposes, is now tested in an applicative case concerning the entrepreneurial propensity of the sampled provinces of Central and Southern Italy, in which an iterative fuzzy k-means method is preliminary used to split them into an optimal number of homogeneous groups.

关键词： Fuzzy discriminant analysis fuzzy clustering linear regression model customer relationship management entrepreneurial propensity

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Measurement Experiment and Mathematical model of Nitrate Ion Selective Electrode

Measurement Experiment and Mathematical Model of Nitrate Ion...

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3rd International Conference on Instrumentation & Measurement, Computer, Communication and Control (IMCCC)

作者： Chang, Zhikai Zhu, Ying Zhang, Li Du, Shangfeng China Agr Univ Coll Informat & Elect Engn Beijing 100094 Peoples R China

ISBN: (纸本)9780769551227

Compared with conventional laboratory chemical analysis, ion selective electrode (ISE) is time-saving, low-cost, ease of use and pollution-free. To detect soil nitrate nitrogen content rapidly, a nitrate ion selective electrode could be used. This paper studied characteristics of nitrate ISE. Potentiometric experiments utilizing nitrate ISE to measure sodium nitrate solution were conducted during the study. A linear regression model based on the Nernst equation was built using the least square method. Several groups of potential values were measured at one concentration and then the arithmetic mean of them was calculated. These mean values and their corresponding concentrations were used in LSM to reduce the impact of the relatively poor repeatability of ISE and reduce nitrate concentration prediction errors. The feasibility of the modeling method was verified using prediction errors as an index. In this study, extra data points except the calibration points were used to test the prediction error. Except several singular points, the relative error of this model was from 1.3% to 13.67% (absolute value). Compared with calibration each time, this modeling method can be used to determinate the nitrate concentration if ISE will be calibrated after using for a certain number of times.

关键词： ion selective electrode nitrate nitrogen measurement experiment linear regression model repeatability

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A Prediction model for Cognitive Performance in Health Ageing Using Diffusion Tensor Imaging with Graph Theory

A Prediction Model for Cognitive Performance in Health Agein...

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35th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Yun, Ruijuan Lin, Chung-Chih Wu, Shuicai Huang, Chu-Chung Lin, Ching-Po Chao, Yi-Ping Chang Gung Univ Dept Comp Sci & Informat Engn Taoyuan Taiwan Beijing Univ Technol Coll Life Sci & Bioengn Beijing Peoples R China Natl Yang Ming Univ Inst Radiol Sci Taipei Taiwan Natl Yang Ming Univ Inst Neurosci Taipei Taiwan

ISBN: (纸本)9781457702167

In this study, we employed diffusion tensor imaging (DTI) to construct brain structural network and then derive the connection matrices from 96 healthy elderly subjects. The correlation analysis between these topological properties of network based on graph theory and the Cognitive Abilities Screening Instrument (CASI) index were processed to extract the significant network characteristics. These characteristics were then integrated to estimate the models by various machine-learning algorithms to predict user's cognitive performance. From the results, linear regression model and Gaussian processes model showed presented better abilities with lower mean absolute errors of 5.8120 and 6.25 to predict the cognitive performance respectively. Moreover, these extracted topological properties of brain structural network derived from DTI also could be regarded as the bio-signatures for further evaluation of brain degeneration in healthy aged and early diagnosis of mild cognitive impairment (MCI).

关键词： Diffusion tensor imaging (DTI) graph theory cognitive abilities screening instrument (CASI) linear regression model Gaussian processes model mild cognitive impairment (MCI)

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El problema de la consultoría está en la t

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Estudios Gerenciales 2013年第126期29卷 118-124页

作者： Julio César Alonso Beatriz Eugenia Gallo Centro de Investigación en Economía y Finanzas Universidad Icesi Cali Colombia

El objetivo de este caso es reforzar la capacidad del lector de aproximarse de forma sistémica a un problema que requiere el uso de herramientas econométricas, en especial la regresión múltiple. Para ello, el problema se contextualiza en una empresa consultora que debe estimar una función de demanda y debe determinar qué pruebas de hipótesis deben hacerse para los coeficientes del modelo de regresión lineal estimado. Esta discusión toca un tema que parece darse por sentado, pero que refleja la necesidad de reflexionar acerca de las razones por las cuales se hace uso de una prueba t individual de 2 colas o de 1 cola y la relación con la teoría económica. This case of study aims to strengthen the ability of the reader to systematically solve issues that involve using econometric tools. We focus on the linear regression model. The problem is about the estimation of a demand curve, which leads to hypothesis testing for a linear regression model. The discussion deals with a problem that seems to be taken for granted, and it also mentions the importance of considering theoretical implications when using one- and two-tailed tests. O objectivo deste caso é reforçar a capacidade do leitor de aproximar-se de forma sistémica de um problema que requer a utilização de ferramentas econométricas, em especial na regressão múltipla. Para tal, o problema é contextualizado numa empresa consultora que deve calcular uma função de procura e deve determinar que provas de hipótese devem ser levadas a cabo para os coeficientes do modelo de regressão linear estimado. Esta discussão toca num tema que parece encarar-se como assente, mas que reflecte a necessidade de reflectir sobre as razões pelas quais se utiliza uma prova de t individual de duas listas ou de uma lista e a relação com a teoria económica.

关键词： modelo de regresión lineal Pruebas t Comparación entre modelos Estimación de demanda linear regression model t -test model comparison Demand estimation modelo de regressão linear Provas t Comparação entre modelos Estimativa de procura

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