Sequential nonparametric estimation of controlled multivariate regression

On Sequential Nonparametric Estimation of Multivariate Lqcation

For the multivariate one-sample location model (relating to a diagonally symmetric distribution). sequential non-parametric (point as well as interval) estimators based on appropriate rank statistics are considered and their asymptotic properties studied. In this context. asymptotic risk-efficiency of the proposed estimators and asymptotic normality of the associated stopping times are establis...

Variance Function Estimation in Multivariate Nonparametric Regression

Variance function estimation in multivariate nonparametric regression is considered and the minimax rate of convergence is established. Our work uses the approach that generalizes the one used in Munk et al (2005) for the constant variance case. As is the case when the number of dimensions d = 1, and very much contrary to the common practice, it is often not desirable to base the estimator of t...

Multivariate Nonparametric Regression

As in many areas of biostatistics, oncological problems often have multivariate predictors. While assuming a linear additive model is convenient and straightforward, it is often not satisfactory when the relation between the outcome measure and the predictors is either nonlinear or nonadditive. In addition, when the number of predictors becomes (much) larger than the number of independent obser...

Estimation of a nonparametric regression spectrum for multivariate time series

Estimation of a nonparametric regression spectrum based on the periodogram is considered. Neither trend estimation nor smoothing of the periodogram are required. Alternatively, for cases where spectral estimation of phase shifts fails and the shift does not depend on frequency, a time domain estimator of the lag-shift is defined. Asymptotic properties of the frequency and time domain estimators...

Nonparametric sequential estimation of zeros and extrema of regression functions