Chaudhuri, Arijit ; Bose, Mausumi ; Ghosh, J. K. (2004) An application of adaptive sampling to estimate highly localized population segments Journal of Statistical Planning and Inference, 121 (2). pp. 175-189. ISSN 0378-3758
Full text not available from this repository.
Official URL: http://linkinghub.elsevier.com/retrieve/pii/S03783...
Related URL: http://dx.doi.org/10.1016/S0378-3758(03)00117-4
Abstract
It is difficult to enumerate the people in India who are engaged in various small-scale industries in the unorganized sector because they are concentrated in small regional pockets. In estimating separately the total numbers of workers earning principally through ten respective single-industries in the unorganized small-scale sector in a specific district in rural India, through numerical illustrations we have two observations to report: (1) A traditional stratified two-stage sampling scheme is ineffective for some of the industries because of failures to capture the earners concentrated in priorly unknown locations. (2) An adaptive sampling scheme extending the initial sample by appropriate 'network' formations based on well-defined 'neighbourhoods' brings about dramatic improvements exploiting clustering tendencies of earners by different industries.
| Item Type: | Article |
|---|---|
| Source: | Copyright of this article belongs to Elsevier Science. |
| Keywords: | Adaptive Sampling; Rao-Hartley-Cochran Scheme; Stratified Two-stage Sampling; Varying Probabilities |
| ID Code: | 22523 |
| Deposited On: | 24 Nov 2010 08:25 |
| Last Modified: | 02 Jun 2011 06:39 |
Repository Staff Only: item control page
