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Linear regression model

Statistical Analysis of Fuzzy Linear Regression Model Based on Centroid Method

Statistical Analysis of Fuzzy Linear Regression Model Based on Centroid Method

... fuzzy linear regression analysis (regression coefficient is clear number) can be transformed into traditional linear regression ...fuzzy linear regression analysis can be ...

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Simple and Multi Linear Regression Model of Verbs in Quran

Simple and Multi Linear Regression Model of Verbs in Quran

... multi-linear regression model of verbs in the Quran book. This model, gives an analysis for the influence to frequency of words with the form (—un, نو---) made by the frequency of plural ...

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An approach to select linear regression model in bioanalytical method validation

An approach to select linear regression model in bioanalytical method validation

... of linear regression model during bioanalytical method ...sion model and to suggest the need for a weighted re- gression model to reduce ...weighted linear regression, the ...

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Modelling and Forecasting of Residential Electricity Consumption in Nigeria Using Multiple Linear Regression Model and Quadratic Regression Model with Interactions

Modelling and Forecasting of Residential Electricity Consumption in Nigeria Using Multiple Linear Regression Model and Quadratic Regression Model with Interactions

... temperature accounted for 87.3% of the total variation in residential electricity consumption while the remaining 12.7% was accounted for by other variables not in the model. The contribution of population ( ߙ ଵ = ...

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Two-stage source tracking method using a multiple linear regression model in the expanded phase domain

Two-stage source tracking method using a multiple linear regression model in the expanded phase domain

... the linear regression model of IPD by adopting a bi-weight function ...a linear regression slope forced unwrap- ping method which recursively adjusted the estimated wrapping frequency ...

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On Inference of the Linear Regression Model with Groupwise Heteroscedasticity

On Inference of the Linear Regression Model with Groupwise Heteroscedasticity

... heteroscedastic linear regression ...and regression is run on these average ...the linear regression model, facing groupwise ...heteroscedastic linear regression ...

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Pile design using Multiple Linear 
		Regression model

Pile design using Multiple Linear Regression model

... Multiple linear regression model was introduced for the design of piles subjected to axial compression load. The design equation represents the relationships between many variable of soil-structure ...

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Prediction of gestational age by ultrasonogram using linear regression model

Prediction of gestational age by ultrasonogram using linear regression model

... This study was carried out to predict the gestational age based on ultrasound measurements of fetal parameters using linear regression model. Patricia M .Dietz et al ., (2007 in their study provided ...

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Prediction of Heart Disease using Multiple Linear Regression Model

Prediction of Heart Disease using Multiple Linear Regression Model

... hybrid model is developed to diagnose heart disease more ...a model is developed by combing the efficient output features of Decision trees, Naive Bayes, Neural Networks and Support Vector Machines and ...

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Optimal Generalized Biased Estimator in Linear Regression Model

Optimal Generalized Biased Estimator in Linear Regression Model

... The paper introduces a new biased estimator namely Generalized Optimal Estimator (GOE) in a multiple linear regression when there exists multicollinearity among predictor variables. Sto- chastic properties ...

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Some aspects of statistical inference in the linear regression model

Some aspects of statistical inference in the linear regression model

... It therefore appears that from a practical point of view, there are few changes of major consequence in the distributions and properties of estimators and the properties of statistical t[r] ...

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Research on environmental prediction based on linear regression model

Research on environmental prediction based on linear regression model

... Environmental prediction in metal mine has been the main problem which interferes with mining working at depth. And its corresponding formation mechanism is so complicated that the environmental prediction theory cannot ...

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The Heteroskedasticity Test Implementation for Linear Regression Model Using MATLAB

The Heteroskedasticity Test Implementation for Linear Regression Model Using MATLAB

... constructing regression models (Econometric toolbox), which gave the authors relief from the duty of programming the standard functions of regression ...

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Robust Regression Diagnostics of Influential Observations in Linear Regression Model

Robust Regression Diagnostics of Influential Observations in Linear Regression Model

... In regression analysis, data sets often contain unusual observations called ...of model building in that they have to be diag- nosed so as to ascertain whether they are influential or ...

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Developing Noise Pollution Linear Regression Model of Una Town

Developing Noise Pollution Linear Regression Model of Una Town

... The measurement instrument used in this study was sound level meter of Class 2, Model SL-1352, manufactured by HTC. Sound level meter SL-1352. All readings were made by SL-1352 sound level meter with calibrated ...

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A Study on Weather Forecasting using Machine Learning in Big Data

A Study on Weather Forecasting using Machine Learning in Big Data

... Linear Regression: Linear regression attempts to model the relationship between two variables by fitting a linear equation to observed ...a linear regression ...

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A Variable Structural Control for a Flexible Plate

A Variable Structural Control for a Flexible Plate

... multiple linear regression model which mixes the fuzzy and crisp predictors in one model called “Mixed Fuzzy Crisp” (MFC) regression model, is ...new model is derived ...

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Logistic regression for circular data

Logistic regression for circular data

... a regression model to represent the relationship between a linear response and a circular ...i.e linear, circular or di- rectional. They also give a circular-linear regression ...

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Prediction of Crop Production through Hybrid Approach using Machine Learning Algorithms

Prediction of Crop Production through Hybrid Approach using Machine Learning Algorithms

... work Linear regression and Random Forest model are used for prediction and result show that accuracy is not very high so proposed a new model which overcome the limitation of Linear ...

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Linear regression in the parameters study of an econometric model

Linear regression in the parameters study of an econometric model

... future. Linear regression was for us, a way that could give us a simple model to measure the impact of characteristics of a dependent variable on one or more well-defined variables; So an economic ...

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