Institution
Indian Agricultural Statistics Research Institute
Facility•New Delhi, India•
About: Indian Agricultural Statistics Research Institute is a facility organization based out in New Delhi, India. It is known for research contribution in the topics: Population & Small area estimation. The organization has 454 authors who have published 870 publications receiving 7987 citations.
Papers published on a yearly basis
Papers
More filters
••
31 Mar 2023••
TL;DR: In this paper, a method has been given for construction of balanced asymmetrical factorial designs of the type (v −t) × 22 by using truncated balanced incomplete block designs obtainable by omitting t treatments.
Abstract: DAS (1960) gave a method of construction of confounded balanced asymmetrical factorial designs of the type v × 22 by using BIB designs. In the present paper a method has been given for construction of balanced asymmetrical factorial designs of the type (v–t) × 22 by using truncated balanced incomplete block designs obtainable by omitting t treatments. Likewise, partially balanced asymmetrical factorial designs can also be obtained by omitting any particular treatment alongwith its first or second associate treatments from the v treatments of a PBIB design. We can get a large number of new designs not available in literature through this technique. These designs are well suited for varietal trials with multiple basals.
••
01 Jan 2021
TL;DR: In the second phase of the sampling design, the sampler cannot allocate the subsample near the places of interest as discussed by the authors, and the traveling costs are increased because the second sample is selected after the first phase sample is completed.
Abstract: ACS introduced by Thompson (1990) has been found appropriate for sampling of rare and clustered populations. But it suffers from drawback of losing control of the final sample size. There have been several suggestions for limiting this final sample size of adaptive cluster samples. In this design, traveling costs are increased because the second phase sample is selected after the first phase sample is completed. In the second phase of the sampling design, the sampler cannot allocate the subsample near the places of interest. The proposed unbiased estimators of the population mean do not take the advantage of the relation between the variable of interest and the auxiliary variable.
••
25 Dec 2022••
TL;DR: In this paper, a simple method of inclusion probability proportional to sizes is proposed for samples of size three units, and it is shown that the variance of the HORVITZ-THOMPSON estimator based on the proposed sampling scheme is uniformly smaller than that of the traditional estimator used in the probability proportional-to-size with replacement sampling.
Abstract: A simple method of inclusion probability proportional to sizes is proposed for samples of size three units. It is shown that the variance of the HORVITZ-THOMPSON estimator based on the proposed sampling scheme is uniformly smaller than that of the customary estimator used in the probability proportional to sizes with replacement sampling. Further, its performance over RAO-HARTLEY-COCHRAN and SAMPFORD sampling schemes has been studied empirically for some of the natural populations.
Authors
Showing all 462 results
Name | H-index | Papers | Citations |
---|---|---|---|
Sunil Kumar | 30 | 230 | 3194 |
Atmakuri Ramakrishna Rao | 21 | 109 | 1803 |
Charanjit Kaur | 20 | 80 | 4320 |
Anil Rai | 20 | 208 | 1595 |
Ranjit Kumar Paul | 17 | 93 | 875 |
Hukum Chandra | 17 | 75 | 825 |
Sudhir Srivastava | 17 | 69 | 1123 |
Krishan Lal | 16 | 68 | 1022 |
Ashish Das | 15 | 146 | 1218 |
Eldho Varghese | 15 | 127 | 842 |
Deepti Nigam | 14 | 29 | 812 |
Mir Asif Iquebal | 14 | 88 | 604 |
Rajender Parsad | 13 | 98 | 799 |
Deepak Singla | 13 | 32 | 422 |
Prem Narain | 13 | 80 | 503 |