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作者： Yingda Yang Management School Lancaster University

The purpose of this paper is to explore the influencing factors of stock *** analysis and ols analysis are used in this *** there are many factors affecting stock returns,this paper uses factor analysis to reduce the dimension of the selected financial indicators and then uses ols regression analysis to further analyze the influencing factors of stock returns according to the results of factor *** paper uses SPSS software to perform factor analysis on 15 financial indicators in the 2021 financial statements of 97 listed companies on the Beijing Stock Exchange in *** the end,the indicator downs to four factors:solvency factor,profitability factor,earnings quality factor,and growth *** use ols regression analysis to analyze the correlation between these four factors and stock *** conclude,the analysis shows that the solvency factor and the earnings quality factor have a prominent positive influence on the stock ***,the growth factor and profitability factor do not show an influence on the stock price.

关键词： Stock Returns Financial Indicators Panel Data Factor analysis ols regression analysis

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From disruption to normalcy: Co-production public service and destination competitiveness

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TOURISM MANAGEMENT 2025年 106卷

作者： Zhang, Yang Fu, Xiaoxiao Zhang, Ye Huang, Tao Macau Univ Sci & Technol Fac Hospitality & Tourism Management Macau Peoples R China Univ Cent Florida Rosen Coll Hospitality Management Orlando FL USA Capital Univ Econ & Business Sch Business Adm Beijing Peoples R China

Drawing upon the interdisciplinary integration of co-production approaches of public service rooted in the public administration science, this study presents a retrospective analysis of the impact of public service and identifies key co-producers of tourism destination competitiveness (TDC) during uncertain periods. Utilizing the mixed qualitative and quantitative analysis of the policies implemented in Macao from 2020 to 2023 and the data from 1109 questionnaire surveys involving stakeholders, this study identifies 22 dimensions of the four types of coproduction public services. This establishes the internal casual effects between the co-production public service and the TDC, which are achieved through diverse combination of co-production public service dimensions and specific co-producers, considering both their asymmetric and symmetric aspects. Our findings offer new insights into the tourism literature on TDC, exploring the conditions facilitated by co-production public service and providing valuable guidance for destination governments in developing public services to enhance TDC.

关键词： Tourism destination competitiveness (TDC) Co -production public service Public service -dominant logic Complexity theory Stakeholders Critical discourse analysis Fuzzy -set qualitative comparative analysis (fsQCA) ols regression analysis

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Rooftop Surface Temperature analysis in an Urban Residential Environment

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REMOTE SENSING 2015年第9期7卷 12135-12159页

作者： Zhao, Qunshan Myint, Soe W. Wentz, Elizabeth A. Fan, Chao Arizona State Univ Sch Geog Sci & Urban Planning GeoDa Ctr Geospatial Anal & Computat Tempe AZ 85287 USA Arizona State Univ Sch Geog Sci & Urban Planning Tempe AZ 85287 USA

The urban heat island (UHI) phenomenon is a significant worldwide problem caused by rapid population growth and associated urbanization. The UHI effect exacerbates heat waves during the summer, increases energy and water consumption, and causes the high risk of heat-related morbidity and mortality. UHI mitigation efforts have increasingly relied on wisely designing the urban residential environment such as using high albedo rooftops, green rooftops, and planting trees and shrubs to provide canopy coverage and shading. Thus, strategically designed residential rooftops and their surrounding landscaping have the potential to translate into significant energy, long-term cost savings, and health benefits. Rooftop albedo, material, color, area, slope, height, aspect and nearby landscaping are factors that potentially contribute. To extract, derive, and analyze these rooftop parameters and outdoor landscaping information, high resolution optical satellite imagery, LIDAR (light detection and ranging) point clouds and thermal imagery are necessary. Using data from the City of Tempe AZ (a 2010 population of 160,000 people), we extracted residential rooftop footprints and rooftop configuration parameters from airborne LIDAR point clouds and QuickBird satellite imagery (2.4 m spatial resolution imagery). Those parameters were analyzed against surface temperature data from the MODIS/ASTER airborne simulator (MASTER). MASTER images provided fine resolution (7 m) surface temperature data for residential areas during daytime and night time. Utilizing these data, ordinary least squares (ols) regression was used to evaluate the relationships between residential building rooftops and their surface temperature in urban environment. The results showed that daytime rooftop temperature was closely related to rooftop spectral attributes, aspect, slope, and surrounding trees. Night time temperature was only influenced by rooftop spectral attributes and slope.

关键词： rooftop UHI MASTER LIDAR ols regression analysis GIS urban environment

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THE IMPORTANCE OF MATHEMATICS BACKGROUND AND STUDENT PERFORMANCE IN A PROPERTY DEGREE

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PACIFIC RIM PROPERTY RESEARCH JOURNAL 2011年第2期17卷 313-328页

作者： Newell, Graeme Mallik, Girijasankar Univ Western Sydney Penrith NSW Australia

This paper investigates the relative importance of a wide range of academic and personal variables that may impact on student performance in a property degree. In particular, the importance of the property students' mathematics background and prior knowledge is assessed. Using a multi-year data set over 2006-2010, regression analysis (ols) and quantile regression analysis are used to quantify the marginal learning effects of specific variables, including mathematics background. This issue is assessed at the overall property student performance level (Grade Point Average (GPA) on completion of property degree) and at the individual property subject level (3 valuation subjects). Mathematics background is seen to be an important determinant of success in the property degree;particularly in the more advanced valuation subjects requiring cashflow analysis. The property education implications are also highlighted.

关键词： Property student performance mathematics background GPA significant factors ols regression analysis quantile regression

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Charging Infrastructure for Electric Vehicles Forecasting: A Study Based on ARIMA Algorithm and ols regression Model

Charging Infrastructure for Electric Vehicles Forecasting: A...

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2024 International Conference on Telecommunications and Power Electronics, TELEPE 2024

作者： Ma, Haoxin Wang, Jiaqi Zhu, Mingkai School of Computer and Control Engineering Qiqihar University Qiqihar China School of Computer Science China University of Geosciences Wuhan China

ISBN: (纸本)9798350369212

This study comprehensively analyzes the future production, sales and charging infrastructure expansion of new energy electric vehicles in China over the next decade, including production, sales and charging infrastructure expansion. The study uses the ARIMA algorithm, combined with industry data analysis, to forecast the future development of the industry. In addition, the impact of new energy vehicles on the traditional automotive industry is analyzed through ols regression analysis to gain insight into the challenges and opportunities brought about by the rise of new energy vehicles. This study provides valuable experience for the development of new energy vehicles and global sustainable development strategies. © 2024 IEEE.

关键词： ARIMA algorithm New energy electric vehicles ols regression analysis

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Discovering Hidden Knowledge and Optimizing the Model by Analyzing Linear regression Assumptions 26

Discovering Hidden Knowledge and Optimizing the Model by Ana...

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26th International Conference on Computer and Information Technology, ICCIT 2023

作者： Tanni, Kaniz Fatema Akter, Yesmin Jamal, Mohammad Kawser Akter, Subrina Patwary, Muhammed J. A. International Islamic University Department of Computer Science & Engineering Chittagong Bangladesh

ISBN: (纸本)9798350359015

Linear regression is the most frequently used regression analysis due to its simplicity in predicting and forecasting. However, because of its parametric approach, it is necessary to test five assumptions before using this technique on a given dataset. Two of these assumptions are critical, such as linearity and multicollinearity. Linearity has significance for representing patterns;whereas, multicollinearity reduces the model's interpretability. If the negligible level of linearity and the most extreme level of multicollinearity are known before applying regression analysis, it saves significant computing time. This study centers around the level of the greatest linearity and negligible multicollinearity expected for model success. Ordinary least squares (ols) regression analysis has been done for this purpose. A thorough investigation of ten UCI datasets reveals that at least 70% linearity is required for the model to perform well, while a maximum of 45% multicollinearity is acceptable. Furthermore, feature engineering is used to enhance the efficiency of the model by prioritizing linearly associated significant features with the target variable and contains no or little multicollinearity concerns. This implies the final model is very close to the assumptions, lead to upgrade the performance of the model. © 2023 IEEE.

关键词： Feature Engineering Linear regression Linearity Machine Learning Multicollinearity ols regression analysis

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Bitcoin: a diversifier, hedge or safe haven: An academic research concerning the risk management properties of bitcoin

Bitcoin: a diversifier, hedge or safe haven: An academic res...

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作者： R. W. J. Hazewinkel Tilburg University

学位级别：硕士

Over the past seven years the cryptocurrency bitcoin has been a topic of interest for researchers, financial analysts and consumers. The uncertainty surrounding the nature of bitcoin and its recognition as a financial asset have yielded numerous papers focusing on these topics. By combining the regression analysis of Baur & Lucey (2010) and the Modern Portfolio Theory (Markowitz, 1952, 1959) in one study, this thesis closes a gap in the literature concerning the risk management properties of bitcoin. This thesis aimed to investigate the diversification, hedge and safe haven properties of bitcoin for a US portfolio including nine assets. The regression results suggest that bitcoin can mainly acts as a diversifier. Despite the high volatility of bitcoin, the low correlation of bitcoin yields diversification benefits for the US portfolio. The results of mean-variance spanning test (Chen et al., 2010) show that inclusion of bitcoin is beneficial for the risk-return trade-off for the US portfolio. Last of all, the application of the Black-Litterman model expresses doubt towards the results of the Modern Portfolio Theory. Nevertheless, additional testing with the Black-Litterman model suggests a small inclusion of bitcoin is beneficial for the US portfolio, these finding are in line with the results of the Modern Portfolio Theory. By summarizing the results above, it can be concluded that the inclusion of bitcoin can improve the performance of a US portfolio. Therefore, this thesis advocates bitcoin should be taken seriously by investors as a financial asset, however investors should stay vigilant of bitcoin's risks.

关键词： Bitcoin diversifier hedge safe haven ols regression analysis Modern Portfolio Theory diversification mean-variance spanning test Black-Litterman model

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The Effect of LEED Certification on Urban Heat Islands

The Effect of LEED Certification on Urban Heat Islands

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作者： Gu, Donghwan Texas A&M University

学位级别：master

Sustainable building performance has become one of the most critical concerns recently, in architecture and urban planning disciplines. Leadership in Energy and Environmental Design (LEED) certification studies have proven that the LEED badge provides certain types of ownership benefits. However, it has not been shown whether or not a LEED certified building also enhances environmental benefits to its surroundings. For example, if LEED certification promises a standard for an environment-friendly building, then a group of these certificates should imply greater environmental benefits to the society. This is the main question of this study. The author answers this question through examining possible relationships of LEED certificates and their influence on outdoor temperature of surroundings. Overall results suggest that both LEED certification levels and the mass effect of LEED buildings do not have significant influence on regional climates in the Texas and Florida States. It should be noted that, however, the State of California resulted in an interesting output as it showed higher negative coefficients for the LEED concentration areas, and all the coefficients showed negative correlation with the regional climate. The modeling results by California State indicate that LEED certified buildings could lower the outdoor temperature by 0.3 Celsius, with Gold and Platinum certifications showing even better reduction capability

关键词： LEED Urban Heat Island Effect Regional Credits Sustainable Architecture Moran?s Index ols regression analysis

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Monitoring Building Deformation with InSAR: Experiments and Validation

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SENSORS 2016年第12期16卷 2182-2182页

作者： Yang, Kui Yan, Li Huang, Guoman Chen, Chu Wu, Zhengpeng Wuhan Univ Sch Geodesy & Geomat Wuhan 430079 Peoples R China Tianjin Inst Surveying & Mapping Tianjin 300381 Peoples R China Chinese Acad Surveying & Mapping Beijing 100830 Peoples R China Tianjin Remote Sensing Ctr Tianjin 300381 Peoples R China

Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas;nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings;the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (ols) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between ols regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated.

关键词： building deformation monitoring InSAR accuracy index validation test ols regression analysis measurement of error analysis

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