ڈاکٹر عبدالمعید خان
جامعہ عثمانیہ حیدرآباد کے شعبہ عربی کے صدر ڈاکٹر عبدالمعید خاں کی وفات علمی حلقہ کے لیے ایک سانحہ ہے، انھوں نے قاہرہ اور کیمبرج میں تعلیم پاکر ساری عمر جامعہ عثمانیہ کی خدمت میں گذاری، کچھ دنوں آکسفورڈ یونیورسٹی میں بھی عربی کے پروفیسر رہے، حیدر آباد کے مشہور انگریزی رسالہ اسلامک کلچر کی ادارت کے فرائض آخر وقت تک بڑی خوبی سے انجام دیئے مارماڈیوک پکتھال نے اس کا جو معیار قائم کیا تھا، اس کو انھوں نے قائم رکھا، دائرۃالمعارف حیدرآباد کی علمی سرگرمیوں میں بھی ان کا بڑا حصہ رہا، ان کی رہنمائی میں یہاں سے بہت سی مفید کتابیں شائع ہوئیں، مولانا ابوالکلام آزاد ان کی علمی صلاحیتوں کے معترف تھے، وہ حکومت کی علمی کمیٹیوں میں نامزد ہوتے رہے، جہاں وہ عزت کی نظر سے دیکھے جاتے تھے، امید ہے کہ جامعہ عثمانیہ ان کو ایک نامور فرزند کی حیثیت سے برابر یاد رکھے گی۔
(صباح الدین عبدالرحمن، نومبر ۱۹۷۳ء)
Shah ʿAbdul Latīf Bhitāī's Kalām (Risāla) is the interpretation of Sharīʿah and Taṣawwuf. Then parables and metaphors are used, but in essence, the whole Risāla is based on the teachings of Ṣūfīsm. Allāh has given acceptance to this Risāla. Many interpretations and explanations of Shāh's Risāla have been written. This article is based on the introduction of an outspoken, commentator who interpreted Shāh Sāḥib's Kalām in the light of Sharīʿah and Ṣūfīsm. It was an important task of its kind. He was not certified scholar or peer or mentor to carry out this work, but he was a headman and land lord. Allāh took this unique work from his pen. The name of this saint is Ḥajī Rasūl Bakhsh Dero. This interpretation of Shāh's Kalām is the one of the biggest argument for this saint's good faith, Sincerity and honesty.
The thesis presents the Bayesian analysis of some two-parameter lifetime distributions in presence of random censoring. It is well known that for the distributions having shape parameter(s), the conjugate joint prior distributions of shape and scale parameters do not exist while computing the Bayes estimates. In this thesis it is assumed that the shape and scale parameters have independent gamma priors. In case of no prior information about the parameters, the commonly used noninformative priors on the shape and scale parameters are considered. It is observed that the closedform expressions for the Bayes estimators cannot be obtained; four different methods of Bayesian computation are proposed in the crucial places to obtain the approximate Bayes estimates. Among these two are based on analytical approximation, namely, the Lindley’s approximation and the Tierney-Kadane’s approximation; and two are based on Monte Carlo sampling that are importance sampling and Gibbs sampling. For each model, we use three different methods of estimation: maximum likelihood, analytical approximation and Monte Carlo sampling. Simulation studies are carried out to observe the behavior of the Bayes estimators and to compare with the maximum likelihood estimators of the unknown parameters, the hazard function and the reliability function for different sample sizes, different priors, different loss functions, different loss function parameter values and for different censoring rates. The analysis of real data examples is performed in a noble way to illustrate the proposed 10 methodology. Several model fitness measures are taken into consideration to check the goodness-of-fit of the proposed models