Nonparametric estimation of the average growth curve with general nonstationary error process

نویسندگان

  • K. Benhenni
  • M. Rachdi
چکیده

The non-parametric estimation of the growth curve has been extensively studied in both stationary and some nonstationary particular situations. In this work, we consider the statistical problem of estimating the average growth curve for a fixed design model with nonstationary error process. The nonstationarity considered here is of a general form, and this note may be considered as an extension of previous results. The optimal bandwidth is shown to depend on the singularity of the autocovariance function of the error process along the diagonal. A Monte Carlo study is conducted in order to assess the influence of the number of subjects and the number of observations per subject on the estimation.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Nonparametric Estimation of Spatial Risk for a Mean Nonstationary Random Field}

The common methods for spatial risk estimation are investigated for a stationary random field. Because of simplifying, lets distribution is known, and parametric variogram for the random field are considered. In this paper, we study a nonparametric spatial method for spatial risk. In this method, we model the random field trend by a local linear estimator, and through bias-corrected residuals, ...

متن کامل

- - Random Approximations to Some Measures of Accuracy in Nonparametric Curve Estimation

SUMMARY This paper deals with a quite general nonparametric statistical curve estimation setting. Special cases include estimation of probability density functions, regression functions and hazard functions. The class of "fractional delta sequence estimators" is defined and treated here. This class includes the familiar kernel, orthogonal series and histogram methods. It is seen that, under som...

متن کامل

Nonparametric estimation via empirical risk minimization

A general notion of universal consistency of nonparametric estimators is introduced that applies to regression estimation, conditional median estimation, curve fitting, pattern recognition, and learning concepts. General methods for proving consistency of estimators based on minimizing the empirical error are shown. In particular, distribution-free almost sure consistency of neural network esti...

متن کامل

Nonparametric Estimation of Nonhomogeneous Poisson Processes Using Wavelets

Nonhomogeneous Poisson processes (NHPPs) are frequently used in stochastic simulations to model nonstationary point processes. These NHPP models are often constructed by estimating the rate function from one or more observed realizations of the process. Both parametric and nonparametric models have been developed for the NHPP rate function. The current parametric models require prior knowledge ...

متن کامل

THE COMPARISON OF TWO METHOD NONPARAMETRIC APPROACH ON SMALL AREA ESTIMATION (CASE: APPROACH WITH KERNEL METHODS AND LOCAL POLYNOMIAL REGRESSION)

Small Area estimation is a technique used to estimate parameters of subpopulations with small sample sizes.  Small area estimation is needed  in obtaining information on a small area, such as sub-district or village.  Generally, in some cases, small area estimation uses parametric modeling.  But in fact, a lot of models have no linear relationship between the small area average and the covariat...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005