Pseudo New Modified Latin Square (NML m (m)) Type PBIB Designs

A New Modified Latin square [NML _i (m)] association scheme with i constraints for v = m ² treatments was introduced by Garg (2008 Garg , D. K. ( 2008 ). New modified Latin square (NMLi) type PBIB designs . J. Math. Syst. Sci. 1 ( 4 ): 83 – 89 . [Google Scholar]). In this article, a new association scheme known as Pseudo New Modified Latin square [Pseudo NML _m (m)] type association scheme is defined. The parameters of Pseudo NML _m (m) association scheme turned out to be parameters of NML _i (m) association scheme by taking i = m in NML _i (m) association scheme. The Pseudo NML _m (m) association scheme will be the usual NML _m (m) association scheme when m is a prime or a prime power. The PBIB designs following Pseudo NML _m (m) association scheme will be called the Pseudo NML _m (m) type PBIB designs. Analysis of Pseudo NML _m (m) designs along with a construction method of these designs is also given in this article.     

Sibling rivalry and the gender gap: evidence from child health outcomes in Ghana

When capital and labor markets are imperfect, choice sets narrow, and parents must choose how to ration available funds and time between their children. One consequence is that children become rivals for household resources. In economies with pro-male bias, such rivalries can yield gains to having relatively more sisters than brothers. Using a rich household survey from Ghana, we find that on average if children had all sisters (and no brothers) they would do roughly 25-40% better on measured health indicators than if they had all brothers (and no sisters). The effects are as large as typical quantity-quality trade-offs, and they do not differ significantly by gender. Received: 22 May 1996 / Accepted: 13 July 1998     

Time series analysis of out patients at Urban Health Centre, Suraj Kund, Meerut

Time series analysis of out-patients at Urban Health Centre, Suraj Kund, Meerut, was done using the out-patient attendance of last five years, with the aim to find out the values to help in coping up with the problem of health administration and management. The least square method and ratio-to-trend method were adopted for calculating the secular trend and seasonal variations respectively. There was an increasing trend in out-patients attendance indicating the increasing popularity of the Urban Health Centre. It was found that in second and third quarter of the year the out-patient attendance increased extraordinarily due to various reasons. The two more aspects of time series, i.e. cyclical trend and irregular flactuation could not be analysed due to their insignificant impact over the health management system.     

Minimum local distance density estimation

We present a local density estimator based on first-order statistics. To estimate the density at a point, x, the original sample is divided into subsets and the average minimum sample distance to x over all such subsets is used to define the density estimate at x. The tuning parameter is thus the number of subsets instead of the typical bandwidth of kernel or histogram-based density estimators. The proposed method is similar to nearest-neighbor density estimators but it provides smoother estimates. We derive the asymptotic distribution of this minimum sample distance statistic to study globally optimal values for the number and size of the subsets. Simulations are used to illustrate and compare the convergence properties of the estimator. The results show that the method provides good estimates of a wide variety of densities without changes of the tuning parameter, and that it offers competitive convergence performance.     

Formulating Contextual Building Regulations for Hill Towns of India: The Case of Shimla

Hill towns of India are best known for their salubrious climate, scenic beauty, picturesque setting and healthy living environment. Hill towns have been experiencing high pressure for development for the last three decades and as a result, are facing numerous problems related to new development that is contextually inappropriate and leads to deteriorated living conditions and poor environmental quality. Most of the issues of existing development are due to contextually inappropriate building regulations, which are formulated without consideration of the geoenvironmental and developmental context of environmentally sensitive hill towns. Moreover, no scientific and systematic approach is followed for the formulation of regulations. A new approach based on various intrinsic characteristics and factors is required for formulation of building regulations in the particular context to hill towns of India. The relevant issues related to building regulations are highlighted in this paper along with the identification of a more suitable building regulatory system for the specific context of hill towns. The article suggests a new approach for the formulation of building regulations for hill towns, based on various intrinsic characteristics and different factors, which are crucial for contextual development in hill towns.     

The distribution of the product of two independent generalized trapezoidal random variables

ABSTRACT

In this article, we derive the probability density function (pdf) of the product of two independent generalized trapezoidal random variables having different supports, in closed form, by considering all possible cases. We also show that the results for the product of two triangular and uniform random variables follow as special cases of our main result. As an illustration, we obtain pdf of product for a suitably constrained set of parameters and plot some graphs using MATLAB, which express variation in pdf with change in different parameters of the generalized trapezoidal distribution.     

Consistent estimation of regression coefficients in ultrastructural measurement error model using stochastic prior information

The problem of consistent estimation of regression coefficients in a multivariate linear ultrastructural measurement error model is considered in this article when some additional information on regression coefficients is available a priori. Such additional information is expressible in the form of stochastic linear restrictions. Utilizing stochastic restrictions given a priori, some methodologies are presented to obtain the consistent estimators of regression coefficients under two types of additional information separately, viz., covariance matrix of measurement errors and reliability matrix associated with explanatory variables. The measurement errors are assumed to be not necessarily normally distributed. The asymptotic properties of the proposed estimators are derived and analyzed analytically as well as numerically through a Monte Carlo simulation experiment.     

Models and algorithms for the design of survivable multicommodity flow networks with general failure scenarios

We consider the design of a multicommodity flow network, in which point-to-point demands are routed across the network subject to link capacity restrictions. Such a design must build enough capacity and diverse routing paths through the network to ensure that feasible multicommodity flows continue to exist, even when components of the network fail. In this paper, we examine several methodologies to optimally design a minimum-cost survivable network that continues to support a multicommodity flow under any of a given set of failure scenarios, where each failure scenario consists of the simultaneous failure of multiple arcs. We begin by providing a single extensive form mixed-integer programming formulation for this problem, along with a Benders decomposition algorithm as an alternative to the extensive form approach. We next investigate strategies to improve the performance of the algorithm by augmenting the master problem with several valid inequalities such as cover constraints, connectivity constraints, and path constraints. For the smallest instances (eight nodes, 10 origin–destination pairs, and 10 failure scenarios), the Benders implementation consumes only 10% of the time required by the mixed-integer programming formulation, and our best augmentation strategy reduces the solution time by another 50%. For medium- and large-sized instances, the extensive form problem fails to terminate within 2 h on any instance, while our decomposition algorithms provide optimal solutions on all but two problem instances.