Polynomial regression
Top PDF Polynomial regression:
TítuloLocal polynomial regression estimation with correlated errors
... degree polynomial to the data via weighted least squares and it presents advantages compared with other kernel nonparametric regression ...estimate regression derivatives and its good minimax ...
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TítuloRecursive local polynomial regression under dependence conditions
... In order to compare several kernel regression smoothers, we have listed in Table 1 the asymptotic expressions for the conditional bias and the conditional variance of the following estim[r] ...
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TítuloAsymptotic properties of Local Polynomial regression with missing data and correlated errors
... Local Polynomial Smoother (ILPS ), consists in using SLPS to estimate the missing observations of the response variable Y ; then, the local polynomial estimator for complete data is applied to the completed ...
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TítuloOn the uniform strong consistency of local polynomial regression under dependence conditions
... nonparametric regression with Þxed design, Roussas in (27) studied a general linear smoother of the regression function and obtained consistency in quadratic mean and strong consistency under several mixing ...
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TítuloLocal polynomial regression smoothers with AR error structure
... such as Tsybakov (1986), Fan (1993), Hastie and Loader (1993), Ruppert and Wand (1994), Fan and Gijbels (1995) and Ruppert et al. (1995). In these papers, the independence of the observations was assumed. Masry (1996b), ...
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Polynomial regression using a perceptron with axo-axonic connections
... Hu and Eberhart [Hu and Eberhart 2002] presented a PSO algorithm. This algorithm bypasses nonfeasible sequences. it also creates a random initial population, in which nonfeasible sequenc[r] ...
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Regression models with MoPs Bayesian networks
... We present a model of Bayesian network for continuous variables, where densities and con- ditional densities are estimated with B-spline MoPs. We use a novel approach to directly obtain conditional densities estimation ...
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Chapter 8 Regression and Correlation doc
... Logistic regression analysis is used to examine relationships between variables when the dependent variable is nominal, even though independent variables are nominal, ordinal, interval, or some mixture ...
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Evolutionary prototype selection for multi output regression
... those that can be obtained using the whole data set [3] . In some cases, this reduction simply attempts to remove outliers and noisy instances, thereby facilitating the learning of a model and even im- proving its ...
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Algebras whose tits form weakly controls the module category
... A strongly simply connected algebra D is said to be pg-critical if it is tame not of polynomial growth but every proper quotient of D is of.. w x polynomial growth.[r] ...
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A characteristic polynomial factorization: extending some matrix eigenvalue estimates
... We estimate a the eigenvalues ofMondrigaand other mixed-sign matrices, which arise in the geometry of immobilization as posed by Kuperberg and Papadimitriou, and which molivateJ this fac[r] ...
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The q-classical polynomials and the q-Askey and Nikiforov-Uvarov Tableaus
... Uvarov, Polynomial Solutions of hypergeometri type dierene Equations. and their lassiation[r] ...
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A Fuzzy Approach to Robust Clusterwise Regression
... the regression error ...estimated regression line). First attempts to fit k = 2 regression lines can be found in [18], that applied this type of procedure in economics, in [21] where these type of ...
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A survey on multi-output regression
... vector regression method by extend- ing the single-output SVR to multiple outputs while maintaining the advantages of a sparse and compact solution using a cost ...
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A literature review on the application of evolutionary computing to credit scoring
... The last years have seen the development of many credit scoring mod- els for assessing the creditworthiness of loan applicants. Traditional credit scoring methodology has involved the use of statistical and mathematical ...
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Polynomial maps with maximal multiplicity and the special closure
... of polynomial systems in general, the multiplicity of polynomial maps is a basic tool in singularity ...a polynomial function f ∈ C [x 1 , ...
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Approximation of measurement of the dedication in research of the universities in Colombia from the knowledge by institution
... This session deals with two special cases that may appear when working with counts. Although both cases are fundamentally different, they have the same element in common: 0. It begins by talking about models that do not ...
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Statistical postprocessing of different variables for airports in Spain using machine learning
... the regression, and in fact, this was done for the case of the precipitation, due to the spatial uncertainty of this variable; however, for the temperature, adding more points would mean losing the high resolution ...
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Summability of orthonormal polynomial series
... We shall use a local form of the Haussdorf~ Young inequality to obtain the basic estimates leading to the summability result announced below as Theorem 1... The.[r] ...
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TítuloNonlinear regression model checking via local polynomial smoothing
... nonlinear regression models based on local polynomial estimation is proposed in this ...mixture regression model for real data coming from a thermal analysis ...
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