Approximation to the distribution of the least squares estimators in two dimensional cosine models by randomly weighted bootstrap.

Recently, Kundu and Gupta (Metrika, 48: 83 C 97, 1998) established the asymptotic normality of the least squares estimators in the two dimensional cosine model. In this paper, we give the approximation to the general least squares estimators by using random weights which is called the Bayesian bootstrap or the random weighting method by Rubin (Annals of Statistics, 9: 130 C 134, 1981) and Zheng (Acta Math. Appl. Sinica (in Chinese), 10 (2): 247 C 253, 1987). A simulation study shows that this approximation works very well. [ABSTRACT FROM AUTHOR]