The present manuscript is an attempt to analyze the consequences of non?response in estimation procedure of population mean. Using the sub-sampling of non-respondent technique, families of factor type estimators have been proposed to estimate the population mean when variable under study represents the sensitive characteristic. Properties of the proposed families of estimators are examined under different randomized response models. The measures of privacy protection and efficiencies of the suggested families of estimators have been calculated and their performances are examined. Results are interpreted and suitable recommendations have been made to the survey practitioners. Keywords: Auxiliary information, Factor type estimator, Non-response, Scramble response, Bias, Mean square error.

  Improved generalized double sampling difference-type and regression-type estimators using single auxiliary variable about first two moments about zero are proposed, their bias and mean square error are found and then comparative studies have been made. First, generalized difference-type estimator is proposed and the optimum values minimizing its mean square error are found but the minimizing optimum values contain some unknown parameters; hence, the alternative is to replace the unknown optimum values by the estimated optimum values depending on sample observations by unbiased or consistent estimators of parameters involved in the optimum values of the generalized difference-type estimator and thus getting the enhanced practical utility estimator known as the practical generalized double sampling regression-type estimator attaining the minimum mean square error of the generalized difference-type estimator for the optimum values.

  Lee et al. (2015) proposed a randomized response model which possesses a Cramer-Rao lower bound of variance than that of suggested by Singh and Sedory (2011) at equal or greater protection of respondents. The proposed method Lee et al. (2015) does not provide explicit expression of the estimator of the population proportion of sensitive attribute ? and it is limited only to simple random sampling with replacement (SRSWR) sampling design. In this paper, we propose the generalization of Lee et al. (2015)?s method for complex survey designs in a unified set up. This is applicable for wider classes of sampling design and estimators. Explicit method for complex survey designs in a unified set up. This is applicable for wider classes of sampling design and estimators. Explicit. Keywords: Complex sampling designs, Randomized response, Relative efficiency.

  The theory of small area statistics is in use for over four decades. The validity has not been examined in the absence of the actual results. The data on TFR which was being calculated at district level using the theory of small area statistics utilizing the information on third and higher order births, have become available through recently conducted Annual Health Survey for EAG States by Office of Registrar General of India. Based on this data, the analysis presented in this paper raises questions on the validity of results using methodology of small area statistics. Even with high values of R2 the results based on small area statistics combined for EAG states match with actual only in about 44 percent of the cases. Further, undertaking analysis at State level using small statistics, matching improves to 54 percent only. Keywords: Annual health survey, Covariates, Higher order births, Total fertility rate, Small area statistics.

  Keywords: Annual health survey, Covariates, Higher order births, Total fertility rate, Small area statistics. correlated with plot positions within a linear block (Keifer and Wynn 1981, Cheng 1983, Stroup and Mulitze 1991, Jacroux 1998, Ahmed et al. 2011). Concept of circular blocks was introduced by Rees (1967). In 1983, Morgan developed the optimality criteria of Cyclic Neighbor balanced designs with correlated observations. These circular neighbor balanced designs require a large number of blocks, specially, for even number of treatments. Construction of circular block designs for even number of treatments with correlated blocks, specially, for even number of treatments. Construction of circular block designs for even number of treatments with correlated blocks, specially, for even number of treatments. Construction of circular block designs for even number of treatments with correlated blocks, specially, for even number of treatments. Construction of circular block designs for even number of treatments with correlated observations with lesser number of blocks is a challenge to researchers. In the present paper, an attempt has been made to construct optimal First order circular block designs with lesser number of blocks considering the correlated observations for even number of treatments. The developed designs are general efficiency balanced (GEB) circular block designs (Das and Ghosh 1985 and Kageyama and Mukerjee 1986) with correlated observations for even (v + 1) number of treatments.The structure of the C- matrix of the design has been derived and A and D-efficiencies of the resultant GEB designs are also obtained for different values of the correlation coefficient ? (0 ? ? ? 1). Keywords: GEB designs, Correlated observations, First order circular neighbor balanced designs.

  With wide application of remote sensing technologies and automatic data collection tools, tremendous amount of spatial and non spatial data of agriculture domain have been collected and stored in large spatial databases. The extraction and comprehension of the knowledge implied by such huge amount of spatial data pose great challenges to the researches involved in the area of Agri-Informatics and computer intelligence. Use of computational intelligence in agriculture is important challenging area for developing tools for mass impact of socio-economic development. The present work deals with the development of an integrated computer intelligent system to extract association rules from spatial databases of land use and slope which provide decision making reference for land use planning. Apriori algorithm is applied on the transaction database generated after preprocessing and analysis of spatial databases using ENVI and ArcGIS tools. The investigation was conducted on the land use and slope data of Udham Singh Nagar district obtained from Agrometeorology department, G.B.P.U.A. & T., Pantnagar. data of Udham Singh Nagar district obtained from Agrometeorology department, G.B.P.U.A. & T., Pantnagar. obtained have been verified by agriculture domain experts. Keywords: Data mining, Spatial data mining, Association rule, Land use.

  In this paper, a methodology has been discussed for estimating gca effects free from sca effects under a row-column set-up for Type III complete diallel mating designs. A class of Mating-Environmental Row-Column (MERC) designs has been obtained which is variance balanced for estimating the contrasts pertaining to gca effects free from sca effects. A macro has been developed using PROC IML of SAS software for generating randomized layout of the MERC designs so constructed. Keywords: Diallel cross, GCA, SCA, Row-column design, Type III CDC, SAS macro.

  Fish cultivation has been medium to earn livelihood from old ages. In the hilly areas due to low temperature, fish cultivation is not as feasible as in plain areas. An attempt has been made to understand the growth and forecast pattern of Carp fish in hilly regions through reparametrization of the existing non-linear growth models viz. Logistic, Gompertz and Von-Bertalanffy. It has been found that partial re-parameterized version of Gompertz model i.e. Gompertz-I model is the best fit under these conditions. It has been illustrated with average growth datasets of common carp fish growth data in polyponds pond environments. Suitability of the models for two months ahead forecasting of fish yield from various ponds have been reported. Keywords: Carp fish, Nonlinear growth models, Re-parametrization, Hougaards measure, Box % bias.

  In this paper an attempt has been made to mode the volatile pulses prices using the VAR-MGARCH approach. The different forms of MGARCH models such as BEKK, CCC and DCC have also been explored. To deal with the presence of excess kurtosis in the series Student-t distribution innovation was also considered. Further, it was empirically found that the MGARCH-DCC model with Student-t distribution was the most suitable among all for modelling the pulses series. Keywords: Volatility, VAR, MGARCH, BEKK, CCC, DCC.

  Indian Council of Agricultural Research (ICAR) is one of the largest national agricultural system in the world with 101 institutes and 71 agricultural universities spread across the country. Following the guidelines of Government of India, ICAR was given responsibility to all the ICAR institutes to develop Results Framework Documents (RFDs) in their institutes. But, there is no web based information system available in ICAR for preparing and reporting the RFDs to the respective subject matter divisions (SMD) based information system available in ICAR for preparing and reporting the RFDs to the respective subject matter divisions (SMD) IASRI developed a web based Results Framework Document Management System (RFDMS) in ICAR to manage RFD activities in ICAR which replaces the existing manual handling of RFD documents. The system consists of 6 input options viz., Section 1 to Section 6 of RFD and each of these sections further constitutes different options that help the user to enter various components of RFD. The RFDMS facilitates institutes to prepare, submit targets and achievements and consolidated reports online and also provides access to officials for effective monitoring and decision making. It is a centralized, automated and uniform reporting tool across access ICAR institutes resulting into improved targets monitoring and decision making. This system leads to IT empowerment and improved information management of RFD in ICAR. Keywords: Results framework document, Document management system, Web based system.

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