Indian Agricultural Statistics Research Institute

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.

Construction of A-optimal balanced treatment incomplete block designs: An algorithmic approach

Abstract: The purpose of this article is to present an algorithm to construct A-optimal balanced treatment incomplete block (BTIB) designs. A number of A-optimal BTIB designs are constructed in the parametri...

Effect of Non‐normality on Response to Selection in small Populations

Abstract: The expressions for the r-th largest standardised deviate have been derived for beta, gamma, exponential and log-normal distributions. Using these expressions the intensities of selection have been computed for different parametric values of the distributions and of p, the proportion saved for samples of size upto 10 and compared with the corresponding values for normal distribution. The normal approximation to beta and gamma distributions is seen to be quite robust in predicting response to selection under moderately heavy and low cullings.

Global classical and weak solutions of the prion proliferation model in the presence of chaperone in a banach space

Abstract: The present work is based on the coupling of prion proliferation system together with chaperone which consists of two ODEs and a partial integro-differential equation. The existence and uniqueness of a positive global classical solution of the system is proved for the bounded degradation rates by the idea of evolution system theory in the state space \begin{document}$ \mathbb{R} \times \mathbb{R} \times L_{1}(Z,zdz). $\end{document} Moreover, the global weak solutions for unbounded degradation rates are discussed by weak compactness technique.

Probability Proportional to Size Sampling

Abstract: In sampling from a finite population, often the value of some auxiliary variable, closely related to the main characteristic of interest, is available for all the units of the population. This normalized value of the auxiliary variable may be taken as a measure of the size of a unit. For example, in agricultural surveys, the area under a crop may be taken as a size measure of farms for estimating the yield of crops. In such situations, sampling the units with probability proportional to size (PPS) measure with replacement or without replacement may be used in place of simple random sampling with replacement or simple random sampling without replacement. Since the units with larger sizes are expected to have a bigger total of Y, it is expected that PPS measure sampling procedures will be more efficient than SRSWOR or SRSWR. Note that sampling units have an unequal probability of selection. In the sequel, we discuss some common unequal probability sampling procedures.

Designing an ELearning system framework for Dog Health Management Trainer

Abstract: ELearning, as an efficient and flexible method of learning, has drawn more and more attention from researchers and practitioners in the past decades. The use of ELearning system is spreading rapidly in today's learning process and it is drastically changing the field of current scenario to get the information. This article describes the framework and methods which will be exploited to disseminate the information on dog health among the dog owners and practitioners. The framework was designed for Dog Health Management Trainer (DHMT) that facilitates users to access Flash application by content. The framework integrates different components of the system viz., user interface, retrieval model, database, knowledge acquisition, domain expert and user. The proposed system would provide detailed stepwise information to dog owners at their doorstep regarding various important aspects of general, nutritional and health care management. Thus, the dog owner's and veterinary practitioners will be able to explore contents as they desired.