Using the Estimated Regression Equation for Estimation
A regression equation for the estimation of VO2 MAX in Nepalese male adults
... CONCLUSIONS Therefore, from the present observations it is concluded that the 20-metre multistage shuttle run test is recommended as a valid method to evaluate aerobic fitness in terms of VO 2max within male (age ...
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Macauba production estimated by regression models.
... bunches using easy-to-measure physical ...multiple regression analysis was used to build regression models for each ...versus estimated data reached determination coefficients (R 2 ) above ...
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An Improved Volumetric Estimation Using Polynomial Regression
... polynomial regression (PR) technique is used to estimate the parameters of the dependent variable having a polynomial relationship with the independent ...Polynomial Regression models (PRM) with the ...
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Nonlinear regression using smooth Bayesian estimation
... The main contribution of this paper is the elaboration of a hierarchical Bayesian model that allows smooth estimation of parameters associated with different temporal signals. The observed signals are assumed to ...
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Comparison of risk prediction using the CKD-EPI equation and the MDRD study equation for estimated glomerular filtration rate
... higher estimated GFR category by the CKD- EPI equation compared with the MDRD Study equation ...CKD-EPI equation compared with the MDRD Study equa- tion was consistent in almost all sub- ...
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Logs Transformation in a Regression Equation
... To arrive at this interpretation, recall that the slope tells us how changes in the predictor affect the response. Since the predictor is in the original units of the problem, we begin by seeing what happens to the ...
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Error Estimation Using Fuzzy Linear Regression Analysis
... statistical regression analysis and fuzzy regression analysis, aims to determine the best-fit model for describing the functional relationship between dependent variables and independent variables by ...
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A Mathematical Model for Estimating Imports and Exports in the Philippines: A Normal Estimation Equation for Multiple Linear Regression
... Regression the data series prior to testing the hypothesized relationships which employed ordinary least squares (OLS) regression technique. Tests for heteroskedasticity and collinearity were done ...
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Robust estimation in structural equation models using Bregman divergences
... be estimated to obtain some quantitative ...squares estimation (as used in regression modelling) since the values of the latent variables are not known for any given observable output ...
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Bootstrap inference in a linear equation estimated by instrumental variables
... In Figure 3 , we consider values of n between 20 and 1280 that increase by factors of approximately √ 2. This figure makes it clear that the somewhat mediocre per- formance of CLR evident in the first two figures is a ...
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Bootstrap inference in a linear equation estimated by instrumental variables
... In Figure 3 , we consider values of n between 20 and 1280 that increase by factors of approximately √ 2. This figure makes it clear that the somewhat mediocre per- formance of CLR evident in the first two figures is a ...
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ESTIMATION OF NONPARAMETRIC ORDINAL LOGISTIC REGRESSION MODEL USING LOCAL MAXIMUM LIKELIHOOD ESTIMATION
... logistic regression is a statistical method used to analyze the ordinal response variable with three or more categories and predictor variables that are categorical or ...functions. Estimation is based on ...
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Probability density function estimation using orthogonal forward regression
... updated using the multiplicative nonnegative quadratic programming algorithm, which has the ability to reduce the model size ...this regression- based approach to effectively construct a sparse kernel ...
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Estimation of Regression Model Using a Two Stage Nonparametric Approach
... exponential regression to fit the ...the estimation approaches from regression theory are useful in building linear or nonlinear relation- ships between the values of the predictors and the corre- ...
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Identification and estimation of nonlinear regression models using control functions
... The plots in Figures 3.1, 3.2, 3.3, and 3.4 display − µ(x, b ·) from equation (3.8) for the first 250 days of elapsed unemployment duration for the different specifications. Figures 3.1 and 3.2 concern the ...
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Regression density estimation using smooth adaptive Gaussian mixtures
... a regression density flexibly so that at each value of the covariates the density is a mixture of normals with the means, variances and mixture probabilities of the components changing smoothly as a function of ...
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Load Estimation and Prediction on Passport Data Using Linear Regression
... Load Estimation And Prediction Using Auto Regression Technique:- In this problem, we desire to estimate or predict the load or the number of passports that can be issued in coming few years based on ...
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Estimation of the Amount of Recombinant Protein A Secretion Using Fuzzy Regression
... and a number of laboratory conditions were provided in order to increase the amount of production and secretion (12-14). For laboratory design of this important protein and achieving the best and the most improved ...
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Consistent Estimation of Linear Regression Models Using Matched Data
... 16 March 2017 Abstract Economists often use matched samples, especially when dealing with earn- ings data where a number of missing observations need to be imputed. In this paper, we demonstrate that the ordinary least ...
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Confidence intervals for the estimated smoothing parameter in nonparametric regression
... Confidence intervals are constructed for the smoothing parameter that minimizes average squared error using the asymptotic distribution of the cross-validation function and by a version [r] ...
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