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Journal articles on the topic 'Multifactor analysis'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Luu, Khoa, Marios Savvides, Tien D. Bui, and Ching Y. Suen. "Compressed Submanifold Multifactor Analysis." IEEE Transactions on Pattern Analysis and Machine Intelligence 39, no. 3 (2017): 444–56. http://dx.doi.org/10.1109/tpami.2016.2554107.

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2

Good, Phillip I. "Analysis of MultiFactor Experimental Designs." Journal of Modern Applied Statistical Methods 8, no. 2 (2009): 355–59. http://dx.doi.org/10.22237/jmasm/1257033660.

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3

Peltomäki, Jarkko. "Investment styles and the multifactor analysis of market timing skill." International Journal of Managerial Finance 13, no. 1 (2017): 21–35. http://dx.doi.org/10.1108/ijmf-04-2015-0095.

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Purpose The purpose of this paper is to present and demonstrate how the use of a multifactor model in the analysis of market timing skill can be misleading because the use of a multifactor model does not suit all investment styles equally well. If the factors of the analysis model do not span the portfolio holdings of a fund with less conventional investment strategy, the use of a multifactor model may even deteriorate the overall inference in measuring the market timing skill of a large sample of funds. Design/methodology/approach This study investigates the limitations of multifactor models

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Aleksandrov, M. T., E. N. Vasil’ev, A. V. Lebedev, G. P. Kuz’min, E. M. Khokhlov, and M. I. Voropaeva. "Multifactor analysis in laser fluorescence diagnostics." Journal of Communications Technology and Electronics 52, no. 4 (2007): 457–61. http://dx.doi.org/10.1134/s1064226907040110.

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5

Kao, Jehng-Jung, and Hung-Yue Lin. "Multifactor Spatial Analysis for Landfill Siting." Journal of Environmental Engineering 122, no. 10 (1996): 902–8. http://dx.doi.org/10.1061/(asce)0733-9372(1996)122:10(902).

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6

Dermody, Orla. "Mucking through multifactor experiments; design and analysis of multifactor studies in global change research." New Phytologist 172, no. 4 (2006): 598–600. http://dx.doi.org/10.1111/j.1469-8137.2006.01921.x.

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7

Garcia Gaona, Robinson Alexander, and Carlos Andres Zapata Quimbayo. "Multifactorial Heath-Jarrow-Morton model using principal component analysis." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 1 (2024): 566. http://dx.doi.org/10.11591/ijece.v14i1.pp566-573.

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In this study, we propose an implementation of the multifactor Heath-Jarrow-Morton (HJM) interest rate model using an approach that integrates principal component analysis (PCA) and Monte Carlo simulation (MCS) techniques. By integrating PCA and MCS with the multifactor HJM model, we successfully capture the principal factors driving the evolution of short-term interest rates in the US market. Additionally, we provide a framework for deriving spot interest rates through parameter calibration and forward rate estimation. For this, we use daily data from the US yield curve from June 2017 to Dece

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8

Alexander, Garcia Gaona Robinson, and Zapata Quimbayo Carlos Andres. "Multifactorial Heath-Jarrow-Morton model using principal component analysis." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 1 (2024): 566–73. https://doi.org/10.11591/ijece.v14i1.pp566-573.

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In this study, we propose an implementation of the multifactor Heath-Jarrow- Morton (HJM) interest rate model using an approach that integrates principal component analysis (PCA) and Monte Carlo simulation (MCS) techniques. By integrating PCA and MCS with the multifactor HJM model, we successfully capture the principal factors driving the evolution of short-term interest rates in the US market. Additionally, we provide a framework for deriving spot interest rates through parameter calibration and forward rate estimation. For this, we use daily data from the US yield curve from June 2017 to Dec

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9

Chib, Siddhartha, and Bakhodir Ergashev. "Analysis of Multifactor Affine Yield Curve Models." Journal of the American Statistical Association 104, no. 488 (2009): 1324–37. http://dx.doi.org/10.1198/jasa.2009.ap08029.

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10

Wu, Xueping. "A conditional multifactor analysis of return momentum." Journal of Banking & Finance 26, no. 8 (2002): 1675–96. http://dx.doi.org/10.1016/s0378-4266(01)00179-0.

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11

Anderson, Seth C., B. Jay Coleman, Cheryl J. Frohlich, and Jeffrey W. Steagall. "A MULTIFACTOR ANALYSIS OF COUNTRY FUND RETURNS." Journal of Financial Research 24, no. 3 (2001): 331–46. http://dx.doi.org/10.1111/j.1475-6803.2001.tb00773.x.

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12

Mao, Tie Zheng, and Ai Hua Mao. "Analysis and Implementation of Multifactor System Estimation." Applied Mechanics and Materials 380-384 (August 2013): 1274–77. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1274.

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How to find most relative factor in multifactor system and how to find the function between relative factors and result are very important. In this paper, Bayes is used to find the most relative factors, then the training dataset is clustered by AGNES(Agglomerative Nesting) , then the section polynomial fitting is used to formulate multiple function for those most relative factors. Finally, this method is applied in the eye sight analysis system, and satisfying results can be obtained.

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13

Vyadro, M. M., A. V. Nikitin, and S. M. Navashin. "Multifactor analysis of immunomodulating action of antibiotics." International Journal of Immunopharmacology 13, no. 6 (1991): 773. http://dx.doi.org/10.1016/0192-0561(91)90316-y.

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14

Abi Jaber, Eduardo, and Omar El Euch. "Multifactor Approximation of Rough Volatility Models." SIAM Journal on Financial Mathematics 10, no. 2 (2019): 309–49. http://dx.doi.org/10.1137/18m1170236.

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15

Zhang, Honghong, Zhenwei Mu, Fan Fan, and Fanqi Li. "Analysis of Multifactor Influence Model on Energy Dissipation Rate of Rough-Strips Energy Dissipator in the Spillway Bend." Advances in Materials Science and Engineering 2022 (September 16, 2022): 1–9. http://dx.doi.org/10.1155/2022/2017448.

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The rough-strips energy dissipator (R-SED) is applied to the bottom of the spillway bend and can play the role of energy dissipation and flow stabilization. In this study, based on 18 sets of orthogonal tests and the principle of dimensional analysis, a multifactor influence model of R-SED’s energy dissipation rate was proposed. A dimensionless factor k was introduced, which can reflect the comprehensive characteristics of the geometric dimensions of R-SEDs. The multifactor influence model of the energy dissipation rate considered nine factors, including bend radius of curvature Rc, bend width

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16

Liu, Shican, Yanli Zhou, Yonghong Wu, and Xiangyu Ge. "Option Pricing under the Jump Diffusion and Multifactor Stochastic Processes." Journal of Function Spaces 2019 (February 3, 2019): 1–12. http://dx.doi.org/10.1155/2019/9754679.

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In financial markets, there exists long-observed feature of the implied volatility surface such as volatility smile and skew. Stochastic volatility models are commonly used to model this financial phenomenon more accurately compared with the conventional Black-Scholes pricing models. However, one factor stochastic volatility model is not good enough to capture the term structure phenomenon of volatility smirk. In our paper, we extend the Heston model to be a hybrid option pricing model driven by multiscale stochastic volatility and jump diffusion process. In our model the correlation effects h

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Mitsel, Arthur, Aliya Alimkhanova, and Marina Grigorieva. "Advancing the multifactor model of Stochastic Frontier Analysis." Eastern-European Journal of Enterprise Technologies 3, no. 4 (111) (2021): 58–64. http://dx.doi.org/10.15587/1729-4061.2021.235316.

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The concept of efficiency is important in economic science; at present, its role in every sector of the economy is growing. Evaluating an enterprise’s efficiency makes it possible to implement a correct and profitable strategy of resource allocation, which shows its potential level Given an annual increase in the number of bankrupt enterprises, the issue of estimating the efficiency of enterprises is relevant for both their owners and managers, as well as for creditors. There are various methods and models for estimating the performance of enterprises. This work has assessed the efficiency of

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18

Solórzano-Taborga, Pablo, Ana Belén Alonso-Conde, and Javier Rojo-Suárez. "Data Envelopment Analysis and Multifactor Asset Pricing Models." International Journal of Financial Studies 8, no. 2 (2020): 24. http://dx.doi.org/10.3390/ijfs8020024.

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Recent literature shows that market anomalies have significantly diminished, while research on market factors has largely improved the performance of asset pricing models. In this paper we study the extent to which data envelopment analysis (DEA) techniques can help improve the performance of multifactor models. Specifically, we test the explanatory power of the Fama and French three-factor model, combined with an additional factor based on DEA, on a sample of 2101 European equity funds, for the period from 2001 to 2016. Accordingly, we first form the fund portfolios that constitute our test a

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19

Mitevska, Mayiana, and Maria Dimitrova. "Prosocial Behavior and Organizational Climate: A Multifactor Analysis." International Journal of Management Studies and Social Science Research 06, no. 06 (2024): 94–98. https://doi.org/10.56293/ijmsssr.2024.5313.

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This publication explores the impact of prosocial behavior within organizational settings, focusing on its connection to organizational climate. Utilizing various empirical and theoretical sources, this paper addresses the key internal and external factors that drive prosocial actions. It presents models for analyzing how supportive behaviors, such as altruism and loyalty, influence and are influenced by organizational climate.

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20

Kumar, Pranesh. "ANALYSIS OF MULTIFACTOR IMPRECISE DATA USING NEUTROSOPHIC STATISTICS." jnanabha 54, no. 01 (2024): 134–40. http://dx.doi.org/10.58250/jnanabha.2024.54117.

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In multifactor experiments, data collected may correspond to the categorical variables, which place individuals/items into one of several groups (categories). The values of a categorical variable are levels for the categories and distribution of a categorical variable lists the count or percent of individuals/items falling into each category. For example, a two-way table describes two categorical variables by arranging counts according to a row variable and a column variable and each combination of values for two variables is called a cell. However, sometimes a few or every cell counts may be

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21

Lee, Jea-Young, and Ho-Guen Lee. "Multifactor Dimensionality Reduction(MDR) Analysis by Dummy Variables." Korean Journal of Applied Statistics 22, no. 2 (2009): 435–42. http://dx.doi.org/10.5351/kjas.2009.22.2.435.

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22

Gómez-Sánchez, Gonzalo, Lorena Alonso, Miguel Ángel Pérez, Ignasi Morán, David Torrents, and Josep Ll Berral. "Exhaustive Variant Interaction Analysis Using Multifactor Dimensionality Reduction." Applied Sciences 14, no. 12 (2024): 5136. http://dx.doi.org/10.3390/app14125136.

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One of the main goals of human genetics is to understand the connections between genomic variation and the predisposition to develop a complex disorder. These disease–variant associations are usually studied in a single independent manner, disregarding the possible effect derived from the interaction between genomic variants. In particular, in a background of complex diseases, these interactions can be directly linked to the disorder and may play an important role in disease development. Although their study has been suggested to help complete the understanding of the genetic bases of complex

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23

Arthur, Mitsel, Alimkhanova Aliya, and Grigorieva Marina. "Advancing the multifactor model of Stochastic Frontier Analysis." Eastern-European Journal of Enterprise Technologies 3, no. 4 (111) (2021): 58–64. https://doi.org/10.15587/1729-4061.2021.235316.

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The concept of efficiency is important in economic science; at present, its role in every sector of the economy is growing. Evaluating an enterprise’s efficiency makes it possible to implement a correct and profitable strategy of resource allocation, which shows its potential level Given an annual increase in the number of bankrupt enterprises, the issue of estimating the efficiency of enterprises is relevant for both their owners and managers, as well as for creditors. There are various methods and models for estimating the performance of enterprises. This work has assessed the efficien

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24

Liu, Guo Hua, Zeng Shan Yin, Zheng Wei Wang, Xiao Song Yao, and Wen Zhe Yang. "Research on Blind Source Separation with Noise Based on Multi Factor Analysis." Applied Mechanics and Materials 644-650 (September 2014): 3947–50. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.3947.

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The pre-processing method of blind source separation based on multifactor analysis is proposed to solve the blind source with noise. Firstly, the shortcomings of existing methods of blind source separation are point out after analyzing their principles. The multifactor analysis is introduced in blind source separation and the maximum likelihood estimate based on expectation maximum is used to estimate the common factor and random error. Finally the FastICA algorithm is used to separate BSS result. The validity and the advantage of this method are illustrated by an example.

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25

Holovko, Serhii. "ANALYSIS OF NON-RIGID PAVEMENT DESIGN OPTIONS USING THE HIERARCHY ANALYSIS METHOD." Dorogi i mosti 2022, no. 25 (2022): 31–39. http://dx.doi.org/10.36100/dorogimosti2022.25.031.

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Abstract Introduction. The study considers the issue of technical and economic analysis of alternative design options of non-rigid pavement. This issue is especially relevant during the repairing and reconstruction of roads, when it is need to consider the reuse of road construction materials, the use of geosynthetic materials, and so on. Problem statement. Experience shows that most designers perform technical and economic analysis by one indicator only- the estimated cost, which is due to the lack of methodology for technical and economic analysis of such technical solutions. In many countri

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26

Lieksnis, Raimonds. "MULTIFACTOR ASSET PRICING ANALYSIS OF THE BALTIC STOCK MARKET." Ekonomika 89, no. 4 (2010): 85–95. http://dx.doi.org/10.15388/ekon.2010.0.964.

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This study investigates whether the Fama–French three-factor asset pricing model is applicable for explaining cross-sectional returns of stocks listed in the Baltic stock exchanges. Findings confirm the validity and economic significance of the three-factor model for the Baltic stock market: only investors who chose to invest in value stocks during the reference period achieved positive returns by matching or beating the returns of the stock market index. The monthly returns of 8 Latvian, 13 Estonian and 27 Lithuanian company stocks are analyzed for the time period from June 2002 till February

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27

Fok, Pak-Wing, Xiuling Yan, and Guangming Yao. "Analysis of credit portfolio risk using hierarchical multifactor models." Journal of Credit Risk 10, no. 4 (2014): 45–70. http://dx.doi.org/10.21314/jcr.2014.183.

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28

Arshanapalli, Bala G., T. Daniel Coggin, and John Doukas. "Multifactor Asset Pricing Analysis of International Value Investment Strategies." Journal of Portfolio Management 24, no. 4 (1998): 10–23. http://dx.doi.org/10.3905/jpm.1998.409650.

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29

Rong, Guiwen, Xu Wang, Hui Xu, and Baiqing Xiao. "Multifactor Regression Analysis for Predicting Embankment Dam Breaching Parameters." Journal of Hydraulic Engineering 146, no. 2 (2020): 04019051. http://dx.doi.org/10.1061/(asce)hy.1943-7900.0001653.

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30

Jorn, Hongsuk, and Jerome Klotz. "The Contrast Algorithm for Unbalanced Multifactor Analysis of Variance." Journal of the American Statistical Association 84, no. 405 (1989): 318–24. http://dx.doi.org/10.1080/01621459.1989.10478772.

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31

Svoboda, Jaroslav, and Martina Novotná. "Multifactor productivity analysis in the sample of agricultural enterprises." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 59, no. 7 (2011): 395–402. http://dx.doi.org/10.11118/actaun201159070395.

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The assessment of Total Factor Productivity (TFP), i.e. inclusion of all factors of production seems to be an easy task. However, its calculation can meet with some difficulties. The calculation of inputs is complicated as different factors of production, which are processes to outputs, has to be transformed to a common factor. The aim of the paper was to analyse relations of efficiency of factors of production measured by factor productivity based on economic profit and returns (profitability) of enterprise measured by the most synthetic profitability indicator (Return on Assets, ROA). A part

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32

Dorčák, Peter, Peter Markovič, and František Pollák. "Multifactor Analysis of Online Reputation of Selected Car Brands." Procedia Engineering 192 (2017): 719–24. http://dx.doi.org/10.1016/j.proeng.2017.06.124.

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Wu, Qiang, Liqing Zhang, and Guangchuan Shi. "Robust Multifactor Speech Feature Extraction Based on Gabor Analysis." IEEE Transactions on Audio, Speech, and Language Processing 19, no. 4 (2011): 927–36. http://dx.doi.org/10.1109/tasl.2010.2070495.

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34

Milstein, Claudio F., and Thomas Shipp. "Multiphonic vocalizations: A multifactor analysis of Tibetan monk chanting." Journal of the Acoustical Society of America 96, no. 5 (1994): 3342. http://dx.doi.org/10.1121/1.410663.

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35

Sharma, A., and S. K. Lenka. "Analysis of QKD multifactor authentication in online banking systems." Bulletin of the Polish Academy of Sciences Technical Sciences 63, no. 2 (2015): 545–48. http://dx.doi.org/10.1515/bpasts-2015-0062.

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Abstract In the present scenario internet usage and the online banking sectors are experiencing spectacular growth. The Internet is the fastest growing banking channel today, both in the fields of corporate and retail banking. Banks prefer their customers to use the online banking facility as it reduces their cost, primarily through labour costs. The online banking system addresses several emerging trends: customers’ demand for anytime, anywhere service, product time-to-market imperatives and increasingly complex back-office integration challenges. Online fraud has become major source of reven

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36

Lu, Qiang, Yifan Ge, Ye Yu, Jie Li, and Jingang Rao. "MDataEE: Analysis and Visualization of Multifactor Time Series Data." Journal of Computer-Aided Design & Computer Graphics 34, no. 10 (2022): 1613–25. http://dx.doi.org/10.3724/sp.j.1089.2022.19501.

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37

Wu, Yijun, and Yuzhuo Xi. "Analysis of Multifactor Fundamentals Stock Selection Based on Backtesting." Advances in Economics, Management and Political Sciences 34, no. 1 (2023): 93–99. http://dx.doi.org/10.54254/2754-1169/34/20231680.

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In recent years, quantitative finance has become a major trend for investing which brings stable returns with controllable risks. Among various different quantitative strategies, multifactorial stock selection strategy based on fundamental data (e.g., financial statements, macro- and micro-economy data) is one of the widely investigated strategies. On this basis, this study chooses Chinese listed company to verify the feasibility and effectiveness of the stock selection strategy. To be specific, the Ricequant platform is utilized to realize the backtesting as well as data retrieving in order t

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38

Ridwan, Ridwan, Sudjarwo Sudjarwo, and Hasan Hariri. "Negative Effect of Local Politics on Multifactor Leadership of Junior High School Principals: Empirical Facts from Indonesia." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 20 (July 14, 2023): 1552–63. http://dx.doi.org/10.37394/23207.2023.20.137.

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This research focuses on investigating and examining the influence of local politics on the multifactor leadership of junior high school principals. The method used is a quantitative survey, with the unit of analysis being principals and teachers as respondents from 15 districts (regencies and cities) in Lampung Province. The data collection instrument used was the standardized multifactor leadership questionnaire in the Indonesian version resulting from the translation from English by an expert in the subject and was then discussed in the Forum Group Discussion to get good readability items.

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39

Karimovich, Tukhliev Bozor. "ECONOMETRIC ANALYSIS OF THE INFLUENCE OF INVESTMENTS ON ECONOMIC GROWTH IN UZBEKISTAN." International Journal of Advance Scientific Research 05, no. 12 (2024): 119–34. https://doi.org/10.37547/ijasr-04-12-20.

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Investments are one of the important factors determining the level of economic growth. The article analyzes the impact of centralized, decentralized investments and investments attracted on the basis of foreign credit on ensuring economic growth in our republic, as well as their econometric modeling. The relationship between investments and the level of economic growth was also analyzed by creating a multifactor econometric model.

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40

Karabiyik, Hande, Franz C. Palm, and Jean-Pierre Urbain. "Econometric Analysis of Panel Data Models with Multifactor Error Structures." Annual Review of Economics 11, no. 1 (2019): 495–522. http://dx.doi.org/10.1146/annurev-economics-063016-104338.

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Economic panel data often exhibit cross-sectional dependence, even after conditioning on appropriate explanatory variables. Two approaches to modeling cross-sectional dependence in economic panel data are often used: the spatial dependence approach, which explains cross-sectional dependence in terms of distance among units, and the residual multifactor approach, which explains cross-sectional dependence by common factors that affect individuals to a different extent. This article reviews the theory on estimation and statistical inference for stationary and nonstationary panel data with cross-s

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41

Mordashev, V. M. "Data planning and analysis for synthesis of multidimensional laws (nonlinear multifactor analysis)." Physics of Atomic Nuclei 73, no. 13 (2010): 2167–79. http://dx.doi.org/10.1134/s1063778810130016.

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Pang, Xun. "Varying Responses to Common Shocks and Complex Cross-Sectional Dependence: Dynamic Multilevel Modeling with Multifactor Error Structures for Time-Series Cross-Sectional Data." Political Analysis 22, no. 4 (2014): 464–96. http://dx.doi.org/10.1093/pan/mpu008.

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Multifactor error structures utilize factor analysis to deal with complex cross-sectional dependence in Time-Series Cross-Sectional data caused by cross-level interactions. The multifactor error structure specification is a generalization of the fixed-effects model. This article extends the existing multifactor error models from panel econometrics to multilevel modeling, from linear setups to generalized linear models with the probit and logistic links, and from assuming serial independence to modeling the error dynamics with an autoregressive process. I develop Markov Chain Monte Carlo algori

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43

Tong, Ying. "Study on the Forming Process Simulation of Alien Wheel." Advanced Materials Research 291-294 (July 2011): 327–30. http://dx.doi.org/10.4028/www.scientific.net/amr.291-294.327.

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The multifactor coupling simulation analysis of alien wheel forming process was performed. As for preforming and final-forming process the metal flowing, the temperature field of dies and billet were analyzed. The temperature varying and heat loss were forecast. Based on archard wear model the single-step wear depth in multifactor coupling conditions was evaluated, which helped to evaluating die life. The process scheme according to simulation results got good test verifying.

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Liu, Shiliang, and Fei Li. "Analysis of Multifactor-Driven Myopia Disease Modules to Guide Personalized Treatment and Drug Development." Computational and Mathematical Methods in Medicine 2022 (May 9, 2022): 1–10. http://dx.doi.org/10.1155/2022/5262259.

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Myopia is recognized as a multifactor, multicascade complex disease. However, people still know little about the pathogenesis of myopia. Therefore, we aim to guide the personalized treatment, drug research, and development of myopia. Here, based on the interaction network of myopia-related genes, this study constructed a multifactor-driven myopia disease module map. We first identified differentially expressed (DE) miRNAs in myopia. Then, we constructed a myopia-related protein interaction network targeted by these DE miRNAs. Further, we clustered the network into modules and identified module

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Heriyanto, Heriyanto, and Olven Manahan. "Analysis and Comparison of Methods Evaluation Process Multifactor Simple Additive Weighting Method In Tilawatil Musabaqah Quran (MTQ) North Sumatra Province." Journal Of Computer Networks, Architecture and High Performance Computing 2, no. 1 (2020): 15–22. http://dx.doi.org/10.47709/cnapc.v2i1.352.

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Zogg, Gregory P., and Burton V. Barnes. "Ecological classification and analysis of wetland ecosystems, northern Lower Michigan, U.S.A." Canadian Journal of Forest Research 25, no. 11 (1995): 1865–75. http://dx.doi.org/10.1139/x95-201.

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We describe an ecological, multifactor approach to wetland classification in which ecosystem types are identified on the basis of the simultaneous integration of physiography, climate, hydrology, soil, and vegetation. Aerial photographs and field reconnaissance were used to characterize the diversity of wetlands of the 4000-ha University of Michigan Biological Station, northern Lower Michigan. Twenty-eight wetland units, including nutrient-rich swamps, ombrotrophic bogs, and many intermediate types, were identified. Eight wetland ecosystems, composing 79% of the total wetland area, were sample

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47

Benagin, Ronald A., and Kymwell R. Hinlayagan. "Leadership Styles and Internal Communication Satisfaction as Predictors of Employee Commitment in Commercial Banks." South Asian Journal of Social Studies and Economics 22, no. 4 (2025): 160–80. https://doi.org/10.9734/sajsse/2025/v22i4992.

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This descriptive-correlational study examined the extent to which multifactor leadership and internal communication satisfaction predict organizational commitment among employees in commercial banks. The research aimed to elucidate the dynamic relationships between leadership practices, communication processes, and employee commitment within the banking sector. Data were collected from 200 employees across 15 commercial banks using validated and adapted survey instruments. Statistical analyses, including mean, standard deviation, Pearson’s r, and multiple regression, were employed to interpret

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48

P., S. Aithal, and Prasad Krishna. "ABCD Analysis of Fingerprint Hash Code, Password and OTP based Multifactor Authentication Model." Saudi Journal of Business and Management Studies 3, no. 1 (2018): 65–80. https://doi.org/10.5281/zenodo.1202336.

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<em>Authentication is the usage of one or multiple mechanisms to show that who you declare or claim to be. Authentication ensures that users are granted to some resources or services after verifying their identity. The essential characteristics of every authentication system are to provide high security for their users. Multifactor authentication model always improves or enhances the security compared to single-factor authentication model. This new model makes use of three factors-biometric Fingerprint Hash code, One Time Password (OTP), and Password. Fingerprints are not fully secret compare

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Kirkilevskiy, S. I., O. N. Sulaieva, A. A. Mashukov, et al. "MULTIFACTOR ANALYSIS OF THE ONCOPROTEINS EXPRESSION DEPENDENCE IN GASTRIC CANCER." World of Medicine and Biology 17, no. 75 (2021): 079. http://dx.doi.org/10.26724/2079-8334-2021-1-75-79-84.

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Kononov, Yurii. "Graphic modeling in the tasks of analysis of multifactor systems." Transaction of Scientific Papers of the Novosibirsk State Technical University, no. 2 (August 31, 2017): 19–26. http://dx.doi.org/10.17212/2307-6879-2017-2-19-26.

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