multiple linear regression
Some Modifications to Calculate Regression Coefficients in Multiple Linear Regression
... a multiple linear regression model, there are instances where one has to update the regression ...calculating regression coefficients in multiple linear regression ...
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Development of Prediction Models for the Mutagenicity of Nitrated PAHs Based on Multiple Linear Regression
... Abstract. Nitrated polycyclic aromatic hydrocarbons (NPAHs) are a family of toxicants wide spreading in the environment. In this study, quantitative structural-activity relationship (QSAR) models were developed for the ...
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An application of robust method in multiple linear regression model toward credit card debt
... are multiple linear regression (MLR) models, MLR models with least quartile difference (LQD) method and MLR models with mean absolute deviation ...
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Modelling and Forecasting of Residential Electricity Consumption in Nigeria Using Multiple Linear Regression Model and Quadratic Regression Model with Interactions
... Quadratic Regression with interaction) gave the highest value of coefficient of determination (r 2) compared with model 1 (the Multiple Linear Regression ...Quadratic Regression with ...
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Determination of critical properties of Alkanes derivatives using multiple linear regression
... of multiple linear regression was applied for the first time to find out the most appropriate molecular descriptors in order to estimate critical temperature, critical pressure and critical volume of ...
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Application of multiple linear regression model in the performance analysis of traffic rules
... Nowadays, the traffic safety problem has become the focus of attention and making a sound and reasonable traffic rules and regulations is the trend. The current study mainly discusses the overtaking and lane-changing ...
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A study of English reading ability based on multiple linear regression analysis
... Any of human being’s acquired ability has its own influences, if the influencing factors of an ability can be scientifically grasped and be fulfilled through practices, then it meets the theorem of “efforts+ ...
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Using a Multiple Linear Regression Model to Calculate Stock Market Volatility
... a multiple linear regression model to predict the price of the S&P 500, some important results are necessary to be taken into account for the current ...
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Comparative Evaluation of Multiple Linear Regression and Support vector Machine aided Linear and Non
... -linear regression in QSAR models. Models obtained from SVM aided non-linear regression were found statistically fit and more predictive than models obtained from multiple linear ...
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Bridge Construction Cost Prediction using Multiple Linear Regression
... using multiple linear regression model, based on data of bridges from Maharashtra state in ...log regression techniques, models for cost/m2 and log of cost/m2 are ...suited regression ...
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Evaluation of Two Noise Level Prediction Models: Multiple Linear Regression and a Hybrid Approach
... land-use regression methods, were used to formulate two noise level prediction models namely, multiple linear regression (MLR) and analytical hierarchy process (AHP)-multiple ...
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Comparison of Solar Radiation Intensity Forecasting Using ANFIS and Multiple Linear Regression Methods
... To determine the performance of the ANFIS method in predicting the intensity of solar radiation, the Multiple Linear Regression (MLR) method is used as a comparison. The performance of both methods ...
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A Study of Factors that Influence students Academic performance: Multiple Linear Regression Modeling Approach
... The purpose of this study to examine the influence of factors on academic performance of students by utilizing the applications of multiple linear regression analysis. A total of 300 secondary ...
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A technique of fuzzy c mean in multiple linear regression model toward paddy yield
... the multiple linear regression model and fuzzy c-means in multiple linear regression technique toward paddy ...both multiple linear regression analysis and ...
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Analysis of Tanzanian Energy Demand using Artificial Neural Network and Multiple Linear Regression
... In the experiment, two predictors were used for the study. They included the artificial neural networks (ANN) with the multilayer perceptron (MLP) architecture and the multiple linear regression ...
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Modeling of Yarn Strength Utilization in Cotton Woven Fabrics using Multiple Linear Regression
... the multiple linear regression method to understand how the change in weave and other fabric parameters influences the percentage utilization of single yarn strength in the fabric (% ...
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Comparison between multiple linear regression and fuzzy C regression models towards scale of health in ICU
... The multiple linear regression (MLR) model is well-known in analyzing linear ...Keywords Multiple linear regression (MLR) model; fuzzy c-regression models (FCRM); ...
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EXAMINATION OF MULTIVARIATE MULTIPLE LINEAR REGRESSION ANALYSIS
... The data from a study conducted in 2013 at the Research and Application Farm of Atatürk University have been used in this study. The body weight and cold carcass weights of the Awassi sheep have been taken as the ...
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Multiple Linear Regression for Extracting Phrase Translation Pairs
... In this paper, phrase translation pairs are extracted based on word alignment results of bilingual sentence pairs and parsing trees of source language sentences. Discriminative features including translation literality, ...
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Pile design using Multiple Linear Regression model
... There is a marked increase in the use of statistic and its methods in representing the complex relationship between factors in geotechnical engineering. In this paper “ Multiple Linear Regression ” ...
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