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ICAR-IASRI Newsletter, January- March, 2014

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Title ICAR-IASRI Newsletter, January- March, 2014
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Creator Director ICAR-IASRI
 
Subject Agricultural Statistics
Design of Experiments
Sample Surveys
Statistical Genetics
Forecasting Techniques
Bioinformatics
Computer Applications
 
Description Not Available
The first supercomputing hub for Indian Agriculture ASHOKA (Advanced Super-computing Hub
for OMICS Knowledge in Agriculture) established at Centre for Agricultural Bioinformatics (CABin),
Indian Agricultural Statistics Research Institute, was dedicated to the Nation by Shri Sharad
Pawar, Honourable Union Minster of Agriculture and Food Processing Industries in presence of
Dr. Charan Das Mahant, Shri Tariq Anwar, Union Minsters of State for Agriculture and Food
Processing Industries and Dr. S Ayyappan, Secretary DARE and D.G. ICAR on 15 January
2014.
ICAR-ERP (Enterprise Resource Planning) system which includes solution for financial project,
human resource, material and payroll management has been implemented in IASRI, IARI,
NAARM, CIFE, NDRI from 1st February 2014 and ICAR HQ and IVRI w.e.f. 26 February 2014. System has been implemented in CPRI, CRRI, NBSS&LUP, CAZRI, CIAE, CSWCRTI, IGFRI, CRIDA, IIHR, CMFRI and NBPGR from April 2014. ICAR-ERP is hosted on IASRI website and can be accessed through URL: http://icarerp.iasri.res.in and it can also be visited through http://www.iasri.res.in/misfms/.
Indian NARS Statistical Computing Portal (http://stat.iasri.res.in/sscnarsportal) has been strengthened by adding the modules of Crossover designs and Estimation of genetic variance-covariance from block designs. With these 2 new additions, now 24 analysis modules are available on this portal which have been classified into four broad categories as: Basic Statistics, Design of Experiments, Multivariate Analysis and Statistical Genetics. Calibration estimators of finite population total for two stage sampling design have been proposed and through empirical evaluation it was found that the proposed estimators were performing better than the usual Horvitz Thompson estimator under two-stage sampling design. Through limited empirical evaluation it was found that all the higher order calibration estimators were also efficient. A general method of constructing row-column design with two rows has been developed for orthogonal estimation of main effects and two factor interaction in minimum number of runs for orthogonal parameterization.
Not Available
 
Date 2017-10-10T06:33:57Z
2017-10-10T06:33:57Z
2014-04-01
 
Type News Letter
 
Identifier Not Available
Not Available
http://krishi.icar.gov.in/jspui/handle/123456789/5403
 
Language English
 
Relation Not Available;
 
Publisher Not Available