On The Pros and Cons of Using Excel for Regression Analysis by Sencer Buzrul

“…Excel has also some nonlinear models such as exponential and power models in it; however, Excel computes linear parameter estimates for those nonlinear models and again optimistic R2 is calculated. …”
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Research on the Liquor Yield Prediction Model Integrating Hybrid Kernel Support Vector Regression and Dung Beetle Optimizer by Qinwen Deng, Yibo Xu, Qiang Han, Suyi Zhang, Xianguo Tuo

“…Based on actual liquor production data, a Multi Kernel Support Vector Regression (MKSVR) prediction model is established using the Stacking model fusion method to improve the model’s generalization ability. …”
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Experimental study on the performance of concrete linear cutting by high pressure water jet by Lan Zhang, Jingyan Lu, Haitao Li, Bo Li

“…Finally, a prediction model for depth and width of groove was developed using the method of regression analysis, followed by validation of the precision and robustness of the model. …”
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Determination of the main factors of the gross regional product level by econometric modeling methods for the totality of regions of the Russian Federation by Yu. S. Ivchenko

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Identification of Wiener Model with Internal Noise Using a Cubic Spline Approximation-Bayesian Composite Quantile Regression Algorithm by Tianhong Pan, Wei Guo, Ying Song, Fujia Yin

“…A cubic spline approximation-Bayesian composite quantile regression algorithm is proposed to estimate parameters and structure of the Wiener model with internal noise. …”
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Association of school leaders’ COVID-19 health literacy with the implementation of health promotion in schools in Germany: a cross-sectional study by Marlene Meyer, Kevin Dadaczynski, Melanie Messer, Orkan Okan

“…In some regression models, the sociodemographic factors age, sex, and school type were also significant factors. …”
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A study on reflective factors of social media marketing activities and its influence on purchase intention of gen z by Deepika K S, Ajay Massand

“…Hence, this study develops a model for measuring SMMA and validates the nomological model by verifying its influence on Purchase Intention. …”
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Correction of TRMM 3B43 Monthly Precipitation Data Using Quantile Regression Model in the Urmia Lake Basin by Sima Kazempour Choursi, Mahdi Erfanian, Hirad Abghari, Mirhassan Miryaghoobzadeh, khadijeh Javan

“…The corrected TRMM data using the quantile regression model has a superior performance, as indicated by KGE values above 0.97. …”
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A Predictive Model of the Photosynthetic Rate of Chili Peppers Using Support Vector Regression and Environmental Multi-Factor Analysis by Bin Li, Bo Qiao, Qianyu Zhao, Dan Yang, Rongcheng Zhu, Zhexuan Wang, Yujie Yang

“…A linear fit between measured and predicted Pn values yielded a slope of 0.992 and an intercept of 0.07, indicating near-perfect agreement and surpassing the performance of the BP, RBF, and RF models. …”
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Strong reciprocal dependencies as exceptions when correlations are weak by M. M. Basimov

“…For the pair of variables “Low self-control – High self-control” and “Trusting – Suspicious”, models of linear regression are also considered. It is built on the basis of a dependence that is far from linear, as shown by Pearson’s coefficient of weak correlation equal to 0.28. …”
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An optimization protocol for MRI examination resource allocation based on demand forecasting and linear programming by Zhongbin Zhou, Hanyu Zhou, Yuanyuan Qiao, Zihan Gao, Ying Yang

“…Integrating the ARIMAX model with the NARX model, an ARIMAX-NARX model had been constructed.The predictive accuracy of these models was then assessed and compared. …”
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Experimental Study on the Effect of Wind Speed on Hail Impacts by Yimin Dai, Yao Deng, Hao Luo, Yanwen Long

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Predicting laboratory solution kit accuracy using artificial intelligence: a data-driven approach by Abdulwahab AL-Deib, Eshraq Alsherif, Husameddin Abuzgaia, Amel Rabti, Ruwaida Rtemi, Salem Elfard, Sheren Njaim

“…The glucose conversion models yielded precise transformations (Biolabo: Y = 1.01X−0.03357; BioScien: Y = 1.141X−13.71), while urea models showed robust consistency (Biolabo: Y = 0.9312X + 1.549; BioScien: Y = 0.7073X + 5.252). …”
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Developing PM₂.₅ mitigation solutions based on the analysis of the relationships between PM₂.₅ concentrations and precursor factors: a case study of Hanoi, Vietnam by Long Ta Bui, Binh Quoc Pham, Tho Thi Be Cao

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Sickness absence rates in NHS England staff during the COVID-19 pandemic: Insights from multivariate regression and time series modelling. by Ewan McTaggart, Itamar Megiddo, John Bowers, Adam Kleczkowski

“…We then develop multivariate linear regression models to estimate COVID-19-related sickness absences. …”
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LASSO Technique Application in Stock Market Modelling: An Empirical Evidence in Indonesia by Budi Setiawan

“…The results suggest that the best model in Indonesia Stock Market data of 2000-2014 is using LASSO techniques due to more simpler and the result of estimation relatively similar with least square regression model.…”
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Distributed Nonparametric and Semiparametric Regression on SPARK for Big Data Forecasting by Jelena Fiosina, Maksims Fiosins

“…The forecasting accuracy of the proposed algorithms is compared with the linear regression model, which is the only forecasting model currently having parallel distributed realization within the SPARK framework to address big data problems. …”
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Assessment of the relationship of number of sertoli cells with number of germ cells, spermatogenic activity and germ cell apoptosis rates in bullsusing different regression models by YAMINA BELKHIRI, SOUHEYLA BENBIA, RAMZI LAMRAOUI

“…Histological and histometric methods were used to process left testes of 36 bulls. Prediction models were constructed using both linear and non-linear regression. …”
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A Model Proposal for Estimate the Approxımate Costs and Contract Fees of Public Education Buildings (School Buildings) by Latif Onur Uğur, Servet Kesim

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Characteristic-curve Drawing and Efficiency Simulation of Motor Based on the Least Square Method by SONG Chao, WANG Wenming, XIE Yongbo, LI Shuanglong, LI Xi, LI Yonghua

“…It presented a multiple linear regression model based on motor efficiency, speed and torque because of narrow raw data and low measuring precision when drawing motor characteristic curves. …”
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