... fuzzy linearregression analysis (regression coefficient is clear number) can be transformed into traditional linearregression ...fuzzy linearregression analysis can be ...
... multi-linearregressionmodel 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 ...
... of linearregressionmodel during bioanalytical method ...sion model and to suggest the need for a weighted re- gression model to reduce ...weighted linearregression, the ...
... 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 = ...
... the linearregressionmodel of IPD by adopting a bi-weight function ...a linearregression slope forced unwrap- ping method which recursively adjusted the estimated wrapping frequency ...
... heteroscedastic linearregression ...and regression is run on these average ...the linearregressionmodel, facing groupwise ...heteroscedastic linearregression ...
... Multiple linearregressionmodel was introduced for the design of piles subjected to axial compression load. The design equation represents the relationships between many variable of soil-structure ...
... This study was carried out to predict the gestational age based on ultrasound measurements of fetal parameters using linearregressionmodel. Patricia M .Dietz et al ., (2007 in their study provided ...
... 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 ...
... The paper introduces a new biased estimator namely Generalized Optimal Estimator (GOE) in a multiple linearregression when there exists multicollinearity among predictor variables. Sto- chastic properties ...
... 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] ...
... 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 ...
... constructing regression models (Econometric toolbox), which gave the authors relief from the duty of programming the standard functions of regression ...
... 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 ...
... 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 ...
... LinearRegression: Linearregression attempts to model the relationship between two variables by fitting a linear equation to observed ...a linearregression ...
... multiple linearregressionmodel which mixes the fuzzy and crisp predictors in one model called “Mixed Fuzzy Crisp” (MFC) regressionmodel, is ...new model is derived ...
... a regressionmodel to represent the relationship between a linear response and a circular ...i.e linear, circular or di- rectional. They also give a circular-linearregression ...
... work Linearregression 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 ...
... future. Linearregression 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 ...