Regression splines
Multivariate adaptive regression splines models for vehicular emission prediction
... Adaptive Regression Splines (MARS) were introduced for fitting the relationship between a set of predictors and dependent variables (Friedman ...piecewise regression technique that can be used to ...
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Integration of association statistics over genomic regions using Bayesian adaptive regression splines
... In the search for genetic determinants of complex disease, two approaches to association analysis are most often employed, testing single loci or testing a small group of loci jointly via haplotypes for their ...
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Geometrically Designed, Variable Knot Regression Splines: Asymptotics and Inference
... with splines of a fixed degree is a linear optimization problem, if the number of knots and their location are ...free-knot regression splines have been ...adaptive regression splines ...
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Geometrically designed, variable knot regression splines: variation diminish optimality of knots
... knot regression splines, named GeDS, has recently been introduced by Kaishev et ...spline regression function and its control polygon, with vertices whose y-coordinates are the regression ...
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Automatic, computer aided geometric design of free-knot, regression splines
... adaptive splines (HAS) of Luo and Wahba ...penalized splines, considered by Eubank (1988), Wahba (1990), Marx and Eilers (1996), Rupert and Carroll (2000), Rupert ...(MDL) regression splines ...
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Audio based Classification of Video Genre Using Multivariate Adaptive Regression Splines
... In this paper, Multivariate Adaptive Regression Splines is presented for automatic video genre classification using only audio features. The experiments have indicated that it produce the classification ...
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Survival Analysis with Multivariate Adaptive Regression Splines using Cox-Snell Residual
... Adaptive Regression Splines (MARS) are a generalization of stepwise linear regression method that is often employed to improve the efficiency of regression ...
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Geometrically designed, variable know regression splines: asymptotics and inference
... with splines of a fixed degree is a linear optimization problem, if the number of knots and their location are ...free-knot regression splines have been ...adaptive regression splines ...
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Modelling subject-specific childhood growth using linear mixed-effect models with cubic regression splines.
... cubic regression splines provide a better fit than linear splines to non-lin- ear growth curves when the number of knots is small, as proposed by us and ...cubic regression splines ...
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Geometrically designed, variable knot regression splines
... One popular solution is to approximate f with an n-th order (degree n − 1) spline function defined on [a, b], by the number and location of its k internal knots and by the coefficients in front of the set of basis ...
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Modeling association between DNA copy number and gene expression with constrained piecewise linear regression splines
... In this paper we develop model selection for piecewise linear regression splines (PLRS) to decipher how DNA copy number abnormalities alter the mRNA gene expression level. In addition, we propose a ...
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Using generalized estimating equations with regression splines to improve analysis of butterfly transect data
... latter’s regression coefficients describe the average population response and only describe the covariance among repeated observations (do not attempt to explain ...
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Geometrically designed, variable knot regression splines
... obtain the cubic fit in Figure 7 (d), which has very good visual quality and low MSE value. The GeD spline fits No 1-3 of Table 5, with number of regression functions k + n = 8, are obtained with the default ...
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Data Mining Techniques for Forecasting the Medical Resource Consumption of Patients with Diabetic Nephropathy Lee et al.
... stepwise regression, multivariate adaptive regression splines (MARS), and support vector repression (SVR) have become popular data mining techniques for forecasting ...multiple regression, ...
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Kernel and regression spline smoothing techniques to estimate coefficient in rates model and its application in psoriasis
... using regression splines and kernel smoothing technique to model the rate ...sion splines are a natural extension of the piece-wise con- stant models described above and have been used recently in ...
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Forecasting Stock Prices With Linear And Nonlinear Settings: A Comparison
... Adaptive Regression Splines (MARS) forecasting models, in estimating, evaluating, and selecting among linear and non-linear forecasting models for economic and financial time ...
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Correction of metabolic acidosis improves insulin resistance in chronic kidney disease
... Linear regression was used to assess the inde- pendent association of treatment and/or metabolic acid- osis correction and HOMA test at study ...same regression model (Table ...applying regression ...
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Incorporating covariates in skewed functional data models
... j=1 [{ Y b i (t i,j , X i ) − Y i (t i,j , X i )} 2 ]/4000. Table 1 illustrates the accuracy in estimating the model components. Firstly, it shows numerical evidence that the proposed approach for estimating the ...
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Comparison of fractional splines with polynomial splines; An Application on under-five year’s child mortality data in Pakistan (1960-2012)
... Among various statistical techniques, linear regression is preferred for analysis due to a number of reasons. Some of these include its simplicity, flexibility for the choice of deduction method and ...
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Comparison of Machine Learning Regression Methods to Simulate NO3 Flux in Soil Solution under Potato Crops
... tion dynamics in suction lysimeters in potato plots receiving different N application rates. Four machine learning function approximation methods were compared: multiple linear regressions, multivariate adaptive ...
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