Inclusive Water Governance: a Global Necessity. Lessons from India

Efficient water management has emerged as a critical challenge of environmental protection and human security in the twenty-first century. Lack of water management affects the hydrological cycle of the earth, leading to a major influence on the livelihood of the people. This paper reviews the enhanced role of IWRM in water management. It discusses the functioning of Integrated Water Resource Management (IWRM) as a global approach to overcome the challenge(s) regarding the efficient management of water. Further, the paper argues for ‘inclusive water governance’ developed at the local level as against IWRM developed at the global level. The paper emphasizes on the approach of inclusive water governance as a practical solution to address the water management crisis in India, in particular, and developing countries, in general. Inclusive water governance is sensitive to equitable access to water, as a human right, and also to sustainability of water, as an important resource.

Testing equality of mean vectors in a one-way MANOVA with monotone missing data

In this study, testing the equality of mean vectors in a one-way multivariate analysis of variance (MANOVA) is considered when each dataset has a monotone pattern of missing observations. The likelihood ratio test (LRT) statistic in a one-way MANOVA with monotone missing data is given. Furthermore, the modified test (MT) statistic based on likelihood ratio (LR) and the modified LRT (MLRT) statistic with monotone missing data are proposed using the decomposition of the LR and an asymptotic expansion for each decomposed LR. The accuracy of the approximation for the Chi-square distribution is investigated using a Monte Carlo simulation. Finally, an example is given to illustrate the methods.     

Traffic engineering of tunnel-based networks with class specific diversity requirements

Tunnel-based networks such as Multi-protocol Label switching (MPLS) are suitable for providing diversity guarantees to different service classes or customers. Based on the number of active tunnels to handle, router capabilities can be taxed due to the limited amount of memory and/or processing power of these routers. In this paper, we present a mixed-integer linear program formulation for a traffic engineering problem where such tunnel restrictions are taken into account in addition to standard capacity constraints while addressing diversity requirement of services. Due to large size of the formulation, we also present an accompanied solution approach based on Lagrangian relaxation and sub-gradient optimization. We then present results towards impact of diversity constraint upon the tunneling and capacity restrictions. We observed that the networks having higher amounts of capacity and demands with higher level of survivability are much more sensitive to number of allowed tunnels in the network. The impact is even more prominent for sparsely-connected, large-sized networks.     

Evaluation of a synthetic method of estimation for small areas

A synthetic estimator is one of the simplest estimators for a small area, and it has several variants. In this paper, a ratio-synthetic estimator is proposed and compared with the existing synthetic estimator (Ghangurde & Singh, 1977) and it is observed that the gain due to stratification in the case of a synthetic estimator reduces proportional to the domain coverage.     

A two-stage procedure for estimating a linear function of K multinormal mean vectors when covariance matrices are unknown

We consider the problem of constructing a fixed-size confidence region for a linear function of mean vectors of k multinormal populations, where all covariance matrices are completely unknown. A two-stage procedure is proposed to construct such a confidence region. It is shown that the proposed two-stage procedure is consistent and its asymptotic property for the expected sample size is also given. A Monte Carlo simulation study is given for an illustration.     

Asymptotic non-null distribution for the locally most powerful invariant test for sphericity

The asymptotic non-null distribution of the locally most powerful invariant test for sphericity is derived under local alternatives and the power is compared with that of the likelihood ratio test, which is admissible (Kiefe and Schwartz (1965)) and has a monotone power function (Carter and Srivastava (1977)). Up to 0(n ^-3/2) the powers are essentially the same.     

A comparison of bootstrap method and Edgeworth expansion in approximating the distribution of sample variance — one sample and two sample cases

The performance of the bootstrap method and the Edgeworth expansion in approximating the distribution of sample variance are compared when the data are from a non-normal population. Both approximations are very good. so long as the parent population is close to normal.     

Cusum procedure for monitoring variability

In this paper, a CUSUM procedure is given for monitoring for a decrease in the variance (process improvement) as well as a two-sided CUSUM which monitors for both increases and decreases in the variance. The observations are assumed to be independent and normally distributed. The procedure is based on the log¬arithm of the likelihood ratio of the probability density functions under the two competing hypotheses. Formulae that approximate the average run length of the CUSUM procedure for detecting an increase (or decrease) in the variance of a normal distribution are given. These formulae, when corrected for the overshoot from the boundary, provide a very accurate approximation     

Balanced 2m factorial designs of resolution v which allow search and estimation of one extra unknown effect, 4 ≤ m ≤ 8

In this paper, we obtain balanced resolution V plans for 2^m factorial experiments (4 ≤ m ≤ 8), which have an additional feature. Instead of assuming that the three factor and higher order effects are all zero, we assume that there is at most one nonnegligible effect among them; however, we do not know which particular effect is nonnegligible. The problem is to search which effect is non-negligible and to estimate it, along with estimating the main effects and two factor interactions etc., as in an ordinary resolution V design. For every value of N (the number of treatments) within a certain practical range, we present a design using which the search and estimation can be carried out. (Of course, as in all statistical problems, the probability of correct search will depend upon the size of “error” or “noise” present in the observations. However, the designs obtained are such that, at least in the noiseless case, this probability equals 1.) It is found that many of these designs are identical with optimal balanced resolution V designs obtained earlier in the work of Srivastava and Chopra.