[PDF] Top 20 Nonparametric Regression Estimation with Mixed Measurement Errors
Has 10000 "Nonparametric Regression Estimation with Mixed Measurement Errors" found on our website. Below are the top 20 most common "Nonparametric Regression Estimation with Mixed Measurement Errors".
Nonparametric Regression Estimation with Mixed Measurement Errors
... one measurement made of blood lead (denoted as W), at a random time during their ...to errors and W is a perturbation of X. In the measurement error literature, this is known as the classical error ... See full document
17
Application of Nonparametric Quantile Regression to Estimating Value at Risk.
... t-distributed errors, CaViaR model with Asymmetric Slope and Indirect ...of nonparametric formation can add benefits in the quantile ...our nonparametric quantile regression model, we have the ... See full document
91
Orthogonal Series Estimation of Nonparametric Regression Measurement Error Models with Validation Data
... any nonparametric method in measurement error regression problem, the quality of the estimator also depends on the discrepancy of the observed ... See full document
12
The consistency for estimator of nonparametric regression model based on NOD errors
... The above estimator was first proposed by Georgiev [1] and subsequently has been studied by many authors. In the independent case, consistency and asymptotic normal- ity have been investigated by Georgiev and Greblicki ... See full document
13
Estimating the Parameters Geographically Weighted Regression (GWR) with Measurement Error
... parametric regression models with the measure- ment error, including ...[2,4]. Nonparametric regression models with the measurement errors have been devel- oped by ...a ... See full document
5
NONPARAMETRIC MIXED RATIO ESTIMATOR FOR A FINITE POPULATION TOTAL IN STRATIFIED SAMPLING
... an estimation approach that does not rely on parametric assumptions in the working model is therefore ...Ratio estimation has been looked at by various researchers, but in different ...of ... See full document
15
Instrumental variables quantile regression for panel data with measurement errors
... recall errors. If the regressors are indeed subject to measurement errors (ME), it is well known that the slope coefficient of the least squares (LS) regression estimator is inconsistent ... See full document
48
On Estimation of Population Coefficient of Variation in Presence of Measurement Errors
... The estimation of ...the estimation of ...a regression type of estimators is used to construct a general class of ratio estimators of ...and regression estimators of ...new regression ... See full document
5
Estimation of Nonparametric Regression Models with Measurement Error Using Validation Data
... [10] Lü, Y.-Z., Zhang, R.-Q. and Huang, Z.-S. (2013) Estimation of Semi-Varying Coef- ficient Model with Surrogate Data and Validation Sampling. Acta Mathematicae Applicatae Sinica English , 29, 645-660. ... See full document
10
Estimation and Inference of Threshold Regression Models with Measurement Errors
... to measurement errors because of data aggregation or for other ...of measurement errors results in inconsistent estimation of parameters in a linear ...the measurement error ... See full document
27
Estimation of Nonparametric Multiple Regression Measurement Error Models with Validation Data
... W = η X + − η v , v ~ N ( ) 0,1 , and η is the standard deviation of the measurement error. Then, trim X and W in [ − 2.5, 2.5 ] and scale to [ ] 0,1 respectively. Only results for η = 0.7 and η = 0.9 are reported ... See full document
12
COSSO-type penalized likelihood method for simultaneous nonparametric regression and model selection in exponential Families
... of nonparametric regression in exponential families, and develop a general algorithm using the iteratively- reweighted least squares (IRLS) estimation ... See full document
29
Berry Esseen bounds of weighted kernel estimator for a nonparametric regression model based on linear process errors under a LNQD sequence
... The concept of LNQD sequence was introduced by Newman [17], who investigated the central limit theorem for a strictly stationary LNQD process, and it subsequently has been studied by many authors. Wang and Zhang [12] ... See full document
12
Bayesian Inference about Some Geometric Aspects of Nonparametric Functions.
... some nonparametric functions in various settings and obtain the corresponding contraction rates for level ...classical nonparametric regression ...binary regression, Poisson regression ... See full document
125
Improving prediction from Dirichlet process mixtures via enrichment
... are dependent. Examples for the law of {P x , x ∈ X } start from the dependent DPs of MacEachern (1999); Gelfand et al. (2005) and include Griffin and Steel (2006); Dunson and Park (2008); Ren et al. (2011); Chung and ... See full document
32
A nonparametric hypothesis test via the Bootstrap resampling
... on nonparametric hypothesis tests has been the approach that approximates the …nite-sample null distribution (f:s:n:d:) of a test statistic by its asymptotic ...serious errors when the empirical ... See full document
24
A Representation Index: Glass Ceilings and Sticky Floors
... Our focus is on the native-born population, and our primary interest is on non-white ethnic minorities. We focus on the native-born population to eliminate the potentially con- founding e¤ects of immigration on the ... See full document
22
Optimal designs for testing the functional form of a regression via nonparametric estimation techniques
... This follows readily by a standard result of approximation theory in Hilbert spaces [see e.g. Achieser (1956), p. 15]. For the constant weight function (in other words: for the homosce- dastic regression model ... See full document
11
Conditional Ordering Using Nonparametric Expectiles
... Nonparametric regression can become unstable if there are many ...interpretative, regression model, it is advisable to reduce the dimension of the covariate space by taking into account the ... See full document
23
Consistency of the Priestley–Chao estimator in nonparametric regression model with widely orthant dependent errors
... and Cheng [11] investigated the basic renewal theorems and complete convergence for random walks with WOD increments; Liu et al. [12] and Chen et al. [13] improved and extended the preceding results; Wang et al. [14] ... See full document
13
Related subjects