ESTIMATING THE COMMON MEAN OF A BIVARIATE NORMAL POPULATION

For estimating the common mean of a bivariate normal distribution, Krishnamoorthy & Rohatgi (1989) proposed some estimators which dominate the maximum likelihood estimator in a large region of the parameter space. We consider some modifications of these estimators and study their risk performance.     

A Class of Experimental Designs Balanced for First Residuals

In this paper a new class of designs involving sequences of treatments balanced for first residual effects has been introduced. These designs require only t experimental units for 2t periods, t being the number of treatments to be tested. A unified method of constructing these designs for all values of t (≥2) along with an appropriate method of analysis is presented. Besides, their efficiency relative to some well known designs is investigated.     

An Improved Procedure of Estimating the Finite Population Mean Using Auxiliary Information in the Presence of Random Non Response

This article deals with the problem of estimation of the finite population mean using auxiliary information in the presence of random non response. Three different situations where random non response occurs either in study variate, or in auxiliary variate, or in both the variates, have been discussed. The asymptotically optimum estimators (AOEs) for each strategy are also identified. Expressions of biases and mean squared errors of the proposed estimators have been derived up to the first degree of approximation. Proposed estimators have been compared with the usual unbiased estimator, ratio estimator, and product estimator in the presence of random non response. Empirical studies are also carried out to show the performance of the proposed estimators over other estimators.     

Optimal block designs for double cross experiments

ABSTRACT

This paper presents systematic methods of construction of optimal block designs for a double cross experiments for both even and odd values of “p” parental lines. The both even and odd values of designs are derived by using initial block of unreduced balanced incomplete block designs and initial block of row–column designs given by Bose et al. (1953 Bose, R.C., Shrikhande, S.S., Bhattacharya, K.N. (1953). On the construction of group divisible incomplete block design. Ann. Math. Stat. 24:167–195.[Crossref] , [Google Scholar]) and Gupta and Choi (1998 Gupta, S., Choi, K.C. (1998). Optimal row-column designs for complete diallel crosses. Commun. Stat. Theory Methods 27(11):2827–2835.[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]), respectively. In this attempt we have found some new universally optimal block designs for double cross experiments.     

Parameter estimation of nonlinear mixed-effects models using first-order conditional linearization and the EM algorithm

Nonlinear mixed-effects (NLME) models are flexible enough to handle repeated-measures data from various disciplines. In this article, we propose both maximum-likelihood and restricted maximum-likelihood estimations of NLME models using first-order conditional expansion (FOCE) and the expectation–maximization (EM) algorithm. The FOCE-EM algorithm implemented in the ForStat procedure SNLME is compared with the Lindstrom and Bates (LB) algorithm implemented in both the SAS macro NLINMIX and the S-Plus/R function nlme in terms of computational efficiency and statistical properties. Two realworld data sets an orange tree data set and a Chinese fir (Cunninghamia lanceolata) data set, and a simulated data set were used for evaluation. FOCE-EM converged for all mixed models derived from the base model in the two realworld cases, while LB did not, especially for the models in which random effects are simultaneously considered in several parameters to account for between-subject variation. However, both algorithms had identical estimated parameters and fit statistics for the converged models. We therefore recommend using FOCE-EM in NLME models, particularly when convergence is a concern in model selection.     

Citizenship Amendment Bill 2016: continuities and contestations with special reference to politics in Assam,India

ABSTRACT

This article is an attempt to unpack how the Citizenship Amendment Bill 2016 that proposed citizenship on the basis of religious affiliation trace its past from narrative rooted in partition and idea of religious identity in determination of citizenship status in India. The act proposes, persons belonging to minority community namely Hindus, Sikhs, Jains, Parsi and Christians from Afghanistan, Bangladesh and Pakistan who have either entered into India without valid travel documents or the validity of their documents have expired are eligible to apply for Indian citizenship by naturalisation in 7 years instead of existing 12 years. Building on existing scholarship, field experience and media reports this article argues proposed citizenship amendment bill that favours citizenship status for persecuted minorities defined primarily as Hindus leaving Muslims is not an attempt to redefine citizenship but reinforce logic that favours narrative of India for Hindus.     

扁平世界中的学习型社区:对中国的分析

中国崛起为先进经济体的可能性为其他国家提供了颇为有趣的发展机遇.本文将主要探讨在地域辽阔、人口众多的中国,能否应用知识政策缩小发达地区和欠发达地区之间的种种差异.本文尤为关注发展学习型社区能否填补知识的鸿沟,弥补发展的差距.根据扁平世界理论,世界可以转化为一个公平的游戏场.中国历史悠久,地缘政治复杂,中国的历史教训为发展中国家众多怀抱梦想的社区提供了各种各样的经验教训.基于这一原因,我们将中国加以个案考察.中国发明了印刷术、火药,开启了足球运动(兹不一一列举),却在其巅峰时期建造了长城(本身就是一个工程上的奇迹),与世隔绝,此后日渐衰微,直至欧洲列强的火炮打开了国门,在沿海设立通商口岸,惊醒了中国人.事实上,已有学者论述,是邓小平的改革开放扭转了这一悲惨状态.此种观点未免过于简单,本文不敢苟同.本文认为,旧中国的衰败,并非由于国门的开放或关闭,而是由于缺少知识和衡量知识的标准.     

Combining Multivariate Bioassays: Accurate Inference Using Small Sample Asymptotics

For several independent multivariate bioassays performed at different laboratories or locations, the problem of testing the homogeneity of the relative potencies is addressed, assuming the usual slope‐ratio or parallel line assay model. When the homogeneity hypothesis holds, interval estimation of the common relative potency is also addressed. These problems have been investigated in the literature using likelihood‐based methods, under the assumption of a common covariance matrix across the different studies. This assumption is relaxed in this investigation. Numerical results show that the usual likelihood‐based procedures are inaccurate for both of the above problems, in terms of providing inflated type I error probabilities for the homogeneity test, and providing coverage probabilities below the nominal level for the interval estimation of the common relative potency, unless the sample sizes are large, as expected. Correction based on small sample asymptotics is investigated in this article, and this provides significantly more accurate results in the small sample scenario. The results are also illustrated with examples.     

‘CRASH’ – TOWARDS A CRITICAL PEDAGOGY OF WHITENESS?

Critical whiteness studies has produced significant analysis of the terrors of white supremacist power. However, in relation to cultural-media studies pedagogy, impassioned calls for the denouncement of whiteness raise troublesome concerns and limits for productively addressing students' racialized identities. I maintain that renouncing whiteness in anti-racist teaching does not adequately connect with commonsense and affective experiences of ‘race’ in everyday life for many students. Through a ‘materialist’ analysis of the film Crash (2005), this article opens up the question of the im/possibility of engaging whiteness from an anti-racist stance that neither condemns nor buttresses white identity. Crash, considered from a reading practice that does not simply dwell on textual meaning and interpretation, offers an opportunity to pedagogically engage with the ambivalent representations of ‘race’ which pervade contemporary culture.