Showing 1 - 10 of 10
For the problems of nonparametric estimation of nonincreasing and symmetric unimodal density functions with bounded supports we determine the projections of estimates onto the convex families of possible parent densities with respect to the weighted integrated squared error. We also describe the...
Persistent link: https://www.econbiz.de/10009579180
We consider the partially linear model relating a response Y to predictors (X,T) with mean function XT β + g(T) when the T's are measured with additive error. We derive an estimator of β by modification local-likelihood method. The resulting estimator of β is shown to be asymptotically...
Persistent link: https://www.econbiz.de/10009657894
Persistent link: https://www.econbiz.de/10009581095
Considering partially linear single-index errors-in-variables model which can be described as Y = n(X T a) + ZT ßo + e when the Z' s are measured with additive errors. The general estimators established in literature are biased when ignoring the measurement errors. We proposed two estimators in...
Persistent link: https://www.econbiz.de/10009582402
Persistent link: https://www.econbiz.de/10001919034
Motivated by an example in nutritional epidemiology, we investigate some design and analysis aspects of linear measurement error models with missing surrogate data. The specific problem investigated consists of an initial large sample in which the response (a food frequency questionnaire, FFQ)...
Persistent link: https://www.econbiz.de/10009631748
In many regression applications both the independent and dependent variables are measured with error. When this happens, conventional parametric and nonparametric regression techniques are no longer valid. We consider two different nonparametric techniques, regression splines and kernel...
Persistent link: https://www.econbiz.de/10009631749
In this paper we consider the polynomial regression model in the presence of multiplicative measurement error in the predictor. Consistent parameter estimates and their associated standard errors are derived. Two general methods are considered, with the methods differing in their assumptions...
Persistent link: https://www.econbiz.de/10009631750
There are three major points to this article: 1. Measurement error causes biases in regression fits. The line one would obtain if one could accurately measure exposure to environmental lead media will differ in important ways when one measures exposure with error. 2. The effects of measurement...
Persistent link: https://www.econbiz.de/10009631751
In many problems one wants to model the relationship between a response Y and a covariate X. Sometimes it is difficult, expensive, or even impossible to observe X directly, but one can instead observe a substitute variable W which is easier to obtain. By far the most common model for the...
Persistent link: https://www.econbiz.de/10009631755