Linear regression
Post-processing through linear regression
... classical linear regression approach of ensemble re- gression is based on ordinary least-square (OLS) ...other linear regression schemes exist which over- come ...sical linear ...
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ANTIMICROBIAL EFFICACY OF CURCUMA ZEDOARIA EXTRACT AS ASSESSED BY LINEAR REGRESSION COMPARED WITH COMMERCIAL MOUTHRINSES
... the linear regression method proposed by Orth (18), evaluating the microbial reduction as a function of the exposure time, considering as effectiveness a ...
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USE OF THE SIMPLE LINEAR REGRESSION MODEL IN MACRO-ECONOMICAL ANALYSES
... This hypothesis is important in establishing the properties of the linear regression model. The values of the factorial characteristic are non-stochastic if each value is related to a family of values of ...
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Egg Hatchability Prediction by Multiple Linear Regression and Artificial Neural Networks
... multiple linear regression statistical method to predict hatchability in an artificial incubation ...multiple linear regression model, which used coefficients determined by minimum square ...
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Increasing Sorption Isotherms Accuracy: Weibull Modelling and Linear Regression
... projects. In fact, it was confirmed that even during the primarily sorption isotherm phase, when both reference and sample cells were isolated, data acquisition and analysis must be conducted in a very rigorous way. When ...
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Um estudo bibliográfico sobre regressão linear com suporte de programação genética / A bibliographic study on linear regression with genetic programming support
... and Linear Regression techniques has been used in different applications, such as scheduling tasks, software and hardware projects, weather forecasting, drug experiments, cancer treatment, food quality ...
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Método da Regressão Linear Múltipla Aplicado na Calibração de Sensores Inerciais/Multiple Linear Regression Method Applied in Calibration of Inertial Sensors
... Inertial Navigation Systems (NIS) use accelerometers and gyroscopes as main sensors. In a NIS, the calculation of a vehicle's position, velocity and heading is performed by processing the signals from gyros and ...
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Neutrosophic Correlation and Simple Linear Regression
... Our main goal of this work is propose a method to calculate the correlation coefficient of neutrosophic sets which lies in [0, 1], give us information for the degree of the relationship between the neutrosophic sets. ...
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Robust algorithms for linear regression and locally linear embedding
... In the numerical datasets, the rows represent instances or elements and the columns are the attributes or variables. Spurious elements can be found in almost any dataset of the real word. The main algorithms proposed to ...
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Evaluation for Long Term PM10 Concentration Forecasting using Multi Linear Regression (MLR) and Principal Component Regression (PCR) Models
... There are 7 parameters in data set before extraction process. Each parameter is explained in terms of its initial eigenvalues and its variance (percentage). The selection of PCs is based on eigenvalues (must greater than ...
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Have primary emission reduction measures reduced ozone across Europe? An analysis of European rural background ozone trends 1996–2005
... Loess regression and linear regression (available in full in Appendix B Fig. B1 and Tables B1–B3 of the Supplement) of annual mean, 5th and 95th percentiles have char- acterised and quan[r] ...
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Trends and Multifractal Analyses of Precipitation Data from Shandong Peninsula, China
... single linear model may not provide an adequate description of the relationship between average annual precipitation and ...piecewise linear regression is more competitive since it is a form of ...
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Luiz Roberto Guimarães Guilherme1 , Fatima Maria de Souza Moreira1 , Nilton Curi1
... Soil properties such as exchangeable Ca, Mg, Al, pH, organic matter, base saturation, potential and effective CEC and P-rem could be predicted with high accuracy by random forest from the data obtained by pXRF, ...
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Analysis of dental caries using generalized linear and count regression models
... of linear regression and logistic regression models, which describes both quantitative and qualitative factors that are ...of Linear Models. The ideas of the theory of Linear Models can ...
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J. Pediatr. (Rio J.) vol.92 número5
... multiple linear regression model was adjusted to each of the six age groups (Table ...The regression coefficients were higher at the age groups of 4 months (ˇ = ...
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Detecting periodicities with Gaussian processes
... Figure 1 Plots of the benchmark test functions, observation points and fitted models. For an improved visibility, the plotting region is limited to one period. The RMSE is computed using a grid of 500 evenly spaced ...
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Intraocular pressure and its correlation with blood gas parameters in crested caracaras (Caracara plancus) anesthetized with isoflurane and sevoflurane
... Linear regression curves indicating the regression of intraocular pressure (IOP) values on arterial carbon dioxide partial pressure (PaCO 2 ) values in crested caracaras ( Caracara plan[r] ...
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Rev. Assoc. Med. Bras. vol.56 número3 en v56n3a14
... Battalion in Blumenau between 1963 to 2007. The sample comprised 600 out of a total of 3000 recruits enlisted over the period. Data were collected from individual enlistment iles on recruits which had been archived by ...
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A Regression Approach for Forecasting Vendor Revenue in Telecommunication Industries
... Regression analysis is a data mining technique that is used to extract models for predicting numbers. It predicts a certain numerical outcome based on a set of given input. One common example is to predict house ...
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Cubic-spline interpolation to estimate effects of inbreeding on milk yield in first lactation Holstein cows
... simple linear regression coefficient. They pro- posed using the linear regression model for estimating the ef- fects of inbreeding, especially for animals less than 10% in- ...a linear ...
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