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Institution

Indian Agricultural Statistics Research Institute

FacilityNew 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
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Journal ArticleDOI
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.
Book ChapterDOI
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.
Journal ArticleDOI
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

NameH-indexPapersCitations
Sunil Kumar302303194
Atmakuri Ramakrishna Rao211091803
Charanjit Kaur20804320
Anil Rai202081595
Ranjit Kumar Paul1793875
Hukum Chandra1775825
Sudhir Srivastava17691123
Krishan Lal16681022
Ashish Das151461218
Eldho Varghese15127842
Deepti Nigam1429812
Mir Asif Iquebal1488604
Rajender Parsad1398799
Deepak Singla1332422
Prem Narain1380503
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20232
202212
2021134
2020107
201951
201868