regression method
Regression method and Cloud computing Technology in the field of Agriculture
... During the development of other countries like China, they used cloud computing which provide early-warning and policy-making based on the agricultural products market, the tracing management of agricultural products ...
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A Preliminary Study on Parkinson’s Disease with Regularized Logistic Regression Method
... new method to investigate the reason that causes Parkinson by data analysis with regularized logistic regression method (this method will be mentioned ...
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An improvement over regression method of estimation
... over regression method of estimation and other existing estima- tors of population mean Y which utilize the information only on population mean of auxiliary variable x ...
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Forecasting gold prices using multiple linear regression method
... In this study, we proposed the development of forecasting model for predicting future gold price using Multiple Linear Regression (MLR). The data used in this study are the Gold Prices (GP) from the London PM Fix ...
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Regularized regression method for genome wide association studies
... selection method developed to handle large p, small n ...penalized method is able to handle a collection of SNPs ...a method that takes into account the LD infor- mation among adjacent SNPs in order ...
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Nonparametric regression method for estimating the error variance in unistage sampling
... following section gives a review of nonparametric regression, states a nonparametric regression based estimator of the total, gives expressions for its bias and variance, and suggests ho[r] ...
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Correcting for Seasonality: 1 The Regression Method, with an Application to Irish Data
... the actual moving average results are corrected for the well-known aberrations at high and low points on the moving average curve, to determine trend, using a method described in Memoran[r] ...
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A Novel Generalized Ridge Regression Method for Quantitative Genetics
... a method that is fast (efficient to per- form), testable (can produce a genome-wide significance thresh- old for association study), deterministic (the same estimates are easy to replicate), and flexible (SNP-specific ...
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Standardisation of rates using logistic regression: a comparison with the direct method
... Logistic regression standardisation can also allow for adjustment by non-lin- ear variables and interactions between ...logistic regression method also allows standardisation when there is missing ...
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Assessment of Surface Friction Characteristics for Egyptian Highways
... single regression method for same 70% of recorded data between friction values and surface layer ages using the ENTER method of regression, it is shown that for desert roads there is a ...
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The Method of Finite Difference Regression
... 2.7. Unbiasedness and Consistency of the Coefficient Estimates In this section I prove that the coefficients estimated by the Finite Difference Regression method as detailed in Section 2.6 are unbiased and ...
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The Mutual Nearest Neighbor Method in Functional Nonparametric Regression
... functional regression method (kNN and MNN), this sample of size 215 was splitted into a learning sample of size 120 and a testing sample of size ...MNN method is ...
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The Effect of Leadership Task Behavior and Relational Behavior on Job Performance: Investigating the Moderating Role of Work Alienation
... hierarchical regression method, firstly, put the demographic variables (education, job cate- gory or business nature) as the first group of predictor variables into regression equation, then put the ...
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Physiochemical features for designing novel B-site APP-cleaving enzyme 1 inhibitor against Alzheimer’s
... Background: Β-site APP-cleaving enzyme 1 (BACE-1) is a target protein for therapeutic treatment of Alzheimer’s disease. Objective: The present work focuses on designing of novel BACE-1 inhibitors by predicting ...
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Application of Cox Regression and Kaplan Meir Estimates in the Survival Rate of Patients
... KM method was developed for precisely this purpose, and when competing risk are not present this method leads to an estimate that is consistent with the desired simple ...
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ChIIntroductiontoRegressionandLeastSquares.pptx
... A Hedonic regression is a method which relates market prices to product characteristics.. The Hedonic regression provides a measure of what the market will bear.[r] ...
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Bootstrap based model selection in subset polynomial regression
... subset regression model and determine the prediction interval for the dependent variable in the polynomial subset regression model if the error has any ...polynomial regression model would be very ...
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A Study on Behavior and Preferences of Individual Investors towards Investments with Special Reference to Delhi NCR
... simple regression, there are only two variables; one variable (defined as independent) is the cause of the behavior of another one (defined as dependent ...variable). Regression interprets what exists ...
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A Simple Method for Variable Selection in Regression with Respect to Treatment Selection
... There are several publications which caution about using stepwise procedures for variable selection (Harrell 2001, Miller 2002, Mundry and Nunn 2009). We understand their concerns but would like to address several of the ...
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An approach to select linear regression model in bioanalytical method validation
... the regression results obtained from the calibra- tion ...linear regression for the calibra- tion curve experiment with heteroscedasticity will gener- ate inaccurate analytical results, especially at a ...
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