Local polynomial regression
Top PDF Local polynomial regression:
TítuloOn the uniform strong consistency of local polynomial regression under dependence conditions
... (14) Opsomer, J.D. Nonparametric regression in the presence of correlated errors. In Mod- elling Longitudinal and Spatially Correlated Data: Methods, Applications and Future Di- rections; Gregoire, T.G., ...
33
TítuloAsymptotic properties of Local Polynomial regression with missing data and correlated errors
... The main objective of this work is the nonparametric estimation of the regression function with correlated errors when observations are missing in the response variable. Two nonparametric estimators of the ...
48
TítuloLocal polynomial regression estimation with correlated errors
... We now illustrate the behavior of weighted local polynomial regression with the data of accumulative (last twelve months) retail price index of Spain. The studied series is of 224 months, from ...
28
An assessment of the impacts of recent food market shocks on food prices using price transmission analysis
... Multivariate Local Polynomial Regression (MLPR) methods, are data driven and do not require any specific assumption about the nature of price ...
140
TítuloWeighted Local Nonparametric Regression with Dependent Errors: Study of Real Private Residential Fixed Investment in the USA
... the regression function using the LPR estimator or the EGLPR estimator with the global smoothing parameters proposed ...the regression function odd order fits are preferable; while higher order ...
25
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 ...
27
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 ...
19
Cofactors and equilibria for polynomial vector fields
... Finally we claim that under the assumptions of statement (c) when G is an exponential factor we need that J(F, G)(p) 6= 0 in order that the conclusion of statement (a) holds. We shall prove the claim. Consider the ...
8
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 ...
26
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 ...
10
Statistical postprocessing of different variables for airports in Spain using machine learning
... The 4 closest grid points to the observation point were searched, and a multivariable regression was performed. Not all the points were land points. For the case of the wind, measured at 10 meters, there is also a ...
15
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 ...
34
A literature review on the application of evolutionary computing to credit scoring
... In the context of the evolutionary approaches to credit scoring, one has a number of scorecards that mutate and blend together according to their fitness function at classification (Fogerty and Ireson 1993). One of the ...
41
The Poincaré Polynomial of a Linear Code
... e polynomial of a linear code. This polynomial is also related to the weights of the codewords but contains more information than the weight ...a polynomial in several variables and gives not only ...
9
TítuloNonparametric inference for neural synchrony under low firing activity
... Of course, the smooth bootstrap and the parametric bootstrap described above can be adapted to this regression context as well. Also, there exist vari- ants that take into account heteroscedasticity (wild ...
196
TítuloLocal polynomial regression smoothers with AR error structure
... fixed regression model with random observation error that follows an AR(1) correlation ...the regression function and its derivatives using a modified version of estimators obtained by weighted local ...
27
Reply to Roberto’s Steiner’s Comments on our Chapter
... Variables in logs. Low frequency movements calculated using a robust version of a local regression using weighted linear least squares and a 2nd degree polynomial model that assigns lower weight to ...
8
A class of polynomial planar vector fields with polynomial first integral
... Section 2 supplies some preliminaries where we define some concepts we shall need, such as first integral, curve with only one place at infinity, WAI polynomial first integral or projective vector field. Section 6 ...
28
A Monte Carlo approach to the effect of noise on local stability in polynomial difference equations
... The local asymptotic stability of stochastically perturbed equations of the form (2), with bounded perturbation, has been considered ...recently, local stability of general nonlinear equations under ...
8