检索结果-内蒙古大学图书馆

Reduced rank regression with matrix projections for high-dimensional multivariate linear regression model

ELECTRONIC JOURNAL OF STATISTICS 2021年第2期15卷 4167-4191页

作者： Guo, Wenxing Balakrishnan, Narayanaswamy Bian, Mengjie McMaster Univ Dept Math & Stat Hamilton ON L8S 4K1 Canada

In this work, we incorporate matrix projections into the reduced rank regression method, and then develop reduced rank regression estimators based on random projection and orthogonal projection in high-dimensional multivariate linear regression model. We propose a consistent estimator of the rank of the coefficient matrix and achieve prediction performance bounds for the proposed estimators based on mean squared errors. Finally, some simulation studies and a real data analysis are carried out to demonstrate that the proposed methods possess good stability, prediction performance and rank consistency compared to some other existing methods.

关键词： Matrix projection reduced rank regression dimension reduction high-dimensional data multivariate linear regression model

来源：评论

学校读者我要写书评

暂无评论

Predicting short-term traffic flow in urban based on multivariate linear regression model

引用

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS 2020年第2期39卷 1417-1427页

作者： Li, Dahui Qiqihar Univ Sch Comp & Control Engn Qiqihar Heilongjiang Peoples R China

In order to overcome the problems of low accuracy and time-consuming of traditional prediction methods for short-term traffic flow in urban, a prediction methods for short-term traffic flow in urban based on multiple linear regression model is proposed. The corresponding data attributes of short-term traffic flow in urban are selected by traffic operation status, and used as the original data of traffic flow prediction. According to the selected attributes, spatial static attributes data and traffic flow dynamic attributes data are collected, and fault data are identified and repaired. A multiple linear regression model for prediction of short-term traffic flow in urban is constructed to realize the prediction of short-term traffic flow in urban. The experimental results show that, compared with other methods, the average prediction accuracy of the proposed method is as high as 98.48%, and the prediction time is always less than 0.7 s, which is shorter.

关键词： multivariate linear regression model short-term traffic flow in urban flow prediction spatial static attributes

来源：评论

学校读者我要写书评

暂无评论

Prediction and Analysis of Aero-Material Consumption Based on multivariate linear regression model 3

Prediction and Analysis of Aero-Material Consumption Based o...

引用

3rd IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Yang, Yanming Naval Aviat Univ Qingdao Campus Qingdao 266041 Peoples R China

ISBN: (纸本)9781538643013

multivariate linear regression model has been widely used in society, economy, technology and science research. In this paper, the mathematic model and calculation method of multivariate linear regression model are introduced. The model test and interval estimation method of multivariate linear regression model is discussed. Aiming at the prediction of aero-material consumption, a multivariate linear regression prediction model of aviation material consumption was constructed by collecting the data of three basic monitoring indicators of aircraft tire consumption from 2001 to 2016. Based on the analysis of the examples, the model was tested and optimized by goodness of fit test, F-test, t-test and residual analysis, finally an accurate and reliable multivariate linear regression model was given. The results show that the linear regression model is feasible and effective for the prediction of aero-material spare parts consumption. The research results provide a realistic and scientific method for forecasting aero-material consumption.

关键词： aero-material consumption multivariate linear regression model prediction model test residual analysis

来源：评论

学校读者我要写书评

暂无评论

multivariate linear regression model for Host Based Intrusion Detection 1

引用

1st International Conference on Computational Intelligence in Data Mining (ICCIDM)

作者： Gautam, Sunil Kumar Om, Hari Indian Sch Mines Dept Comp Sci & Engn Dhanbad 826004 Bihar India

ISBN: (纸本)9788132222026;9788132222019

Computer security is an important issue for an organization due to increasing cyber-attacks. There exist some intelligent techniques for designing intrusion detection systems which can protect the computer and network systems. In this paper, we discuss multivariate linear regression model (MLRM) to develop an anomaly detection system for outlier detection in hardware profiles. We perform experiments on performance logfiles taken from a personal computer. Simulation results show that our model discovers intrusion effectively and efficiently.

关键词： Intrusion detection system multivariate linear regression model Mean square error Host based intrusion detection system Network based intrusion detection system

来源：评论

学校读者我要写书评

暂无评论

multivariate linear regression models for predicting metal content and sources in leafy vegetables and human health risk assessment in metal mining areas of Southern Jharkhand, India (Jan, 10.1007/s11356-021-12494-9, 2021)

引用

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2021年第21期28卷 27261-27261页

作者： Giri, Soma Mahato, Mukesh Kumar Singh, Abhay Kumar Cent Inst Min & Fuel Res CSIR Nat Resources & Environm Management Grp Barwa Rd Dhanbad 826015 Bihar India

A Correction to this paper has been published:

关键词： Metals Leafy vegetables Health risk assessment multivariate linear regression model

来源：评论

学校读者我要写书评

暂无评论

Asymptotics of M-estimator in multivariate linear regression models for a class of random errors

引用

AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS 2023年第3期65卷 262-285页

作者： Wu, Yi Yu, Wei Wang, Xuejun Chizhou Univ Chizhou Peoples R China Anhui Univ Hefei Peoples R China

It is known that linear regression models have immense applications in various areas such as engineering technology, economics and social sciences. In this paper, we investigate the asymptotic properties of M-estimator in multivariate linear regression model based on a class of random errors satisfying a generalised Bernstein-type inequality. By using the generalised Bernstein-type inequality, we obtain a general result on almost sure convergence for a class of random variables and then obtain the strong consistency for the M-estimator in multivariate linear regression models under some mild conditions. The result extends or improves some existing ones in the literature. Moreover, we also consider the case when the dimension $p$ tends to infinity by establishing the rate of almost sure convergence for a class of random variables satisfying generalised Bernstein-type inequality. Some numerical simulations are also provided to verify the validity of the theoretical results.

关键词： almost sure convergence asymptotic properties Bernstein-type inequality M-estimator multivariate linear regression model strong consistency

来源：评论

学校读者我要写书评

暂无评论

model of baseline clinicopathological features predicts non-resolution of drug-induced liver injury at 6 months

引用

HEPATOLOGY INTERNATIONAL 2025年 1-14页

作者： Bihari, Chhagan Sharma, Shvetank Giri, Apoorva Yadav, Raj Pal Baweja, Sukriti Rastogi, Archana Sarin, Shiv Kumar Inst Liver & Biliary Sci Dept Pathol D1 Vasant Kunj New Delhi 110070 India Inst Liver & Biliary Sci Dept Mol & Cellular Med D1 Vasant Kunj New Delhi India Krishna Mohan Med Coll & Res Ctr Mathura India Inst Liver & Biliary Sci Dept Hepatol D1 Vasant Kunj New Delhi India

Introduction Chronicity in drug-induced liver injury (DILI) is assessed at 12 months, leading to a large time gap from its initial presentation. In this study, we developed a model that could predict biochemical non-resolution in DILI (DILI-NR) patients at 6 months using baseline clinicopathological data. Patients and methods Cases of DILI with liver biopsies were enrolled between January 2016 and December 2021. BSEP, MDR3, and MRP2 were assessed immunohistochemically. DILI-NR was considered a biochemical non-resolution 6 months after the onset of DILI. A separate cohort of 126 patients was taken as a validation cohort. Results DILI-NR was noted in 59/407 patients (14.5%). DILI-NR patients had significantly higher body mass index, lower hemoglobin, more severe disease at the presentation, autoantibody positivity, higher IgG, association with co-morbidities, and were more aged. Pathologically, DILI-NR had increased ductular reaction, duct damage, duct loss, ductular bile plugs, and autoimmune hepatitis-like morphology along with lesser expression of canalicular transporters. On multivariate logistic regression (LR) analysis and XGBoost analysis, BMI, hemoglobin, presence of autoantibodies, disease severity at baseline, and lower expression of any one transporter were associated with DILI-NR (AUROC = 0.92). After calibrating the model on the test cohort, the LR model showed AUROC of 0.89 with an accuracy of 87.3% and precision of 91.5%, confirming the effectiveness of the model. Conclusion The model encompassing hemoglobin, BMI, presence of autoantibodies, disease severity, and reduced expression of canalicular proteins at baseline predicts the biochemical non-resolution of DILI at six months.

关键词： DILI Chronic DILI Biochemical non-resolution DILI BMI Autoantibody Canalicular transporters Liver pathology Ductular bile plugs Duct damage multivariate linear regression model

来源：评论

学校读者我要写书评

暂无评论

The effect of traffic at speed bumps in residential areas on noise and air pollution

引用

ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH 2023年第33期30卷 80945-80962页

作者： AlKheder, Sharaf Kuwait Univ Coll Engn & Petr Civil Engn Dept POB 5969 Kuwait 13060 State Of Kuwait Kuwait

Although transportation systems are an increasing necessity in today's connected world, the over-reliance on internal combustion engine vehicles has caused an increase in air and noise pollution. Air and noise pollutions are among the negative environmental factors that contribute to disease occurrence due to their negative health consequences. Literature has showed that air and noise pollutions were responsible for thousands of premature deaths in Europe. This has pushed scientists to search for models to calculate the effect of traffic on air and noise pollution, to help predict future scenarios, and to work on ways to mitigate that increase in pollution. In this paper, a statistical model is done by using data measured for 25 speed bump locations in Kuwait, which included traffic flow data in the form of vehicle count and classification, as well as noise level measurements taken through an Amprobe SM20 sound meter, in addition to air pollutant data obtained from the Environment Public Authority (EPA) in Kuwait. The results of the multivariate linear regression model showed that high traffic counts resulted in significantly higher noise levels, reaching more than 70 decibels in certain locations, which is considered unhealthy for extended time periods. The model also showed that sulfur dioxide levels were impacted by both light and heavy vehicles, while particulate matter less than 10 mu m was affected mainly by heavy vehicles. An online survey on speed bumps was completed by 803 participants to understand the behavior of people at speed bumps in Kuwait and understand if age and gender might be a predictor of how people would behave, and this was done by doing Pearson's chi-squared correlation tests on the results obtained from the survey.

关键词： Traffic flow Speed bumps Noise Air pollution multivariate linear regression model Survey

来源：评论

学校读者我要写书评

暂无评论

Synthesis of biodiesel from the composite oil and process parameters optimization using artificial neural network

引用

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING 2024年

作者： Kalos, Pritam S. Kharat, Reena Vivekanandan, Nallu Kannan, Rajeswari Balamurugan, Samraj MIT Acad Engn Sch Mech Engn Pune Maharashtra India Pimpri Chinchwad Coll Engn Dept Comp Engn Pune Maharashtra India Pimpri Chinchwad Coll Engn Dept Mech Engn Pune Maharashtra India Sri Krishna Coll Engn & Technol Dept Mech Engn Coimbatore Tamil Nadu India

This study aims to investigate the effect of catalyst utilization (wt%), methanol to composite oil molar ratio (mole) and reaction thermal state (degrees C) on the biodiesel yield percentage of transesterification of novel composite oil (equal volume % of Castor oil, Mahua oil and dairy waste scum oil). Artificial neural network (ANN) based on central composite design was implemented to investigate the influence of catalyst utilization (1-3 wt%), methanol to composite oil molar ratio (6-12 molar) and reaction thermal state (55-65 degrees C) as the independent variables. Levenberg-Marquardt algorithm was used to predict the responses, biodiesel yield %. The fairness of the ANN prediction of biodiesel yield % is tested by means of coefficients of determination of training phase, validation set, test set and combined training, validation and test. The results revealed that the optimum catalyst utilization, methanol to composite oil molar ratio and reaction thermal state were determined as 3 wt%, 9 molar, and 65 degrees C for the maximum biodiesel yield of 94 +/- 1% from the composite oil. The ASTM D6751 standard is employed to assess the quality of biodiesel derived from a blend of oils. The findings of this study indicate that the newly developed mixed oil is a viable feedstock for the production of biodiesel.

关键词： Biodiesel transesterification composite oil ANN multivariate linear regression model

来源：评论

学校读者我要写书评

暂无评论

Determinants of the performance of private equity backed SMEs: an empirical analysis at the European level

引用

Economic Research-Ekonomska Istrazivanja 2024年第1期37卷

作者： Gigante, Gimede Cesare, Nora Di Cerri, Andrea Finance Department Bocconi University (Italy) Milan Italy

This paper extends previous research to investigate the determinants of the operating performance of small and medium-sized enterprises (SMEs) backed by private equity (PE). The paper is based on a sample of 208 unique private equity-backed firms operating at the European level. A multivariate linear regression model is estimated, in which the private equity-backed firms’ operating performance—as measured by ROA, Revenues/Total Assets, and EBIT/Total Assets—is a function of a variety of factors. These include whether or not the firm is an SME, the presence of family shareholders, and various features specific to the expertise of the private equity investor, as well as the industry, country, and years covered. The analysis is limited to private equity deals that occurred in the European Region between 2005 and 2017. According to the results, the effectiveness of private equity in improving the operating performance of target companies in the three years post-investment is impacted by whether or not the backed firm is an SME. This research paper aims to further existing publications on the link between the involvement of the private equity investor and the status of the backed firm as an SME. © 2024 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： financial crisis and covid-19 impacts multivariate linear regression model operating performance determinants Private equity SMEs

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：