On Two-Stage Non-Parametric Estimation

Two stage non-parametric approach for small area estimation

Small area estimators commonly borrow strength from other related areas. These indirect estimators use models (explicit or implicit) that relate the small areas through supplementary data. Various unit-level and area-level small area models are proposed in the literature, but all these models assume the small area mean is linearly related with supplementary information. In this article, we prop...

Notes on Non-parametric estimation

To tie up the discussion on the topic op estimation, more specifically spectral estimation, we derive here some tighter properties related to the direct use of the Fourier Transform, as contrasted to the properties of parametric methods such as the Levinson-Schur algorithm, where parameters of a model are estimated. We shall obtain a better insight in how well the Fourier Transform on discrete ...

Estimation in a Semi-parametric Two-stage Renewal Regression Model.

We discuss estimation in a two-stage modulated renewal process designed for analysis of paired data on a single individual. We consider a model with proportional hazard intensities. U-process methods are used to show consistency and asymptotic normality of the parameter estimates.

Two-stage estimation using copula function

‎Maximum likelihood estimation of multivariate distributions needs solving a optimization problem with large dimentions (to the number of unknown parameters) but two‎- ‎stage estimation divides this problem to several simple optimizations‎. ‎It saves significant amount of computational time‎. ‎Two methods are investigated for estimation consistency check‎. ‎We revisit Sankaran and Nair's bivari...

Non–parametric volatility estimation