On Mean Estimation Using a Generalized Class of Chain Type Estimator under Successive Sampling
Pp. 31-46 (16)
The present paper comprises a significantly generalized class of chain type
estimators to estimate the population means on the current occasion under the
framework of successive sampling based on auxiliary information on both the
occasion. The proposed generalized class constitutes two renowned chain type classes
proposed by Singh and Vishwakarma [1, 2]. As its particular case, an improvement
over their notion, with some eased regularity conditions, is proposed by us, which
consists of chain type regression estimators additionally to chain type ratio estimators.
The construction of the proposed class is fruitful in the sense of constructing the chain
type classes of estimators in the realm of successive sampling. In terms of efficiency,
we provide a comparative study of the proposed class oversample mean estimator,
Cochran's estimator , Sukhatme et al. estimator  and Singh’s estimator .
A numerical illustration is demonstrated in support of the proposed class.
Auxiliary information, Generalized class of chain type estimator,
Optimum replacement policy, Successive sampling.