Estimation in a semiparametric panel data model with nonstationarity

In this paper, we consider a partially linear panel data model with nonstationarity and certain cross-sectional dependence. Accounting for the explosive feature of the nonstationary time series, we particularly employ Hermite orthogonal functions in this study. Under a general spatial error dependence structure, we then establish some consistent closed-form estimates for both the unknown parameters and the unknown functions for the cases where N and T go jointly to infinity. Rates of convergence and asymptotic normalities are established for the proposed estimators. Both the finite sample performance and the empirical applications show that the proposed estimation methods work well.     

Construction of more Flexible and Efficient P–rep Designs

Early generation variety trials are very important in plant and tree breeding programs. Typically many entries are tested, often with very few resources available. Unreplicated trials using control plots are popular and it is common to repeat the trials at a number of locations. An alternative is to use partially replicated (p–rep) designs, where a proportion of the test entries are replicated at each location. We extend a method for the generation of p–rep designs based on α–arrays to allow for a much broader class of designs to be constructed. Updating procedures for the average efficiency factor and its upper bound are developed for application to the computer generation of efficient p–rep designs.     

Least Trimmed Squares Estimator in the Errors-in-Variables Model

We propose a robust estimator in the errors-in-variables model using the least trimmed squares estimator. We call this estimator the orthogonal least trimmed squares (OLTS) estimator. We show that the OLTS estimator has the high breakdown point and appropriate equivariance properties. We develop an algorithm for the OLTS estimate. Simulations are performed to compare the efficiencies of the OLTS estimates with the total least squares (TLS) estimates and a numerical example is given to illustrate the effectiveness of the estimate.