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آئو چھو لو آسمان

آئوچھو لوآسمان
نحمدہ ونصلی علی رسولہ الکریم امّا بعد فاعوذ بااللہ من الشیطن الرجیم
بسم اللہ الرحمن الرحیم
معزز اساتذہ کرام اور میرے ہم مکتب ساتھیو!
آج مجھے جس موضوع پر اظہار خیال کرنا ہے وہ ہے:’’آئو چھولو آسمان ‘‘
صدرِذی وقار!
آسمان بلندی و عظمت کی علامت ہے، عروج و ترقی کی علامت ہے، مجدی و سروری کی علامت ہے، آسمان کے ذکر سے مقام و مرتبہ مراد لیا جارہا ہے، آسمان کی مثال سے غرض و غایت علو مرتبت ہے، آسمان تک رسائی گویا ترقی و عروج کی معراج ہے۔
صدرِمحترم!
ہمیں عظمت کے حصول کے لیے غفلت و لاپرواہی کے پردے کو تار تار کرنا ہو گا۔ تساہل و کسلمندی کے حصار سے باہر آنا ہوگا ،سستی اور بے کاری کے رجحان کی نفی کرنی ہوگی ، اخلاقی گراوٹ کی غلاظت کی سٹرانڈ سے بچنا ہو گا، زندگی کے تمام پہلوئوں میں مثبت تبدیلی لانا ہوگی۔
جنابِ صدر!
حصول عظمت کی خاطر انتھک محنت کرنا ہوگی ، سلف صالحین کے طریقے اپنانے ہوں گے، دھوکہ دہی ، فریب کاری، کذب بیانی ، ڈاکہ زنی ، زنا کاری ، رشوت ستانی،اقرباء پروری جیسی قبیح عادات سے اپنے دامن کو پاک و صاف رکھنا ہو گا۔ جسم کی صفائی کے ساتھ ساتھ اپنے روح کی بھی طہارت کا انتظام کرنا ہوگا۔
عقابی روح جب بیدار ہوتی ہے جوانوں میں
نظر آتی ہے ان کو اپنی منزل آسمانوں میں
جنابِ صدر!
جن نابغۂ روزگار ہستیوں نے اپنے دامن کو منزّہ مطہر رکھا، جنہوں نے سلف صالحین کے نقش قدم پر چل کر اپنی منازل کا تعین کیا، جنہوں نے ہرلمحہ اپنی زندگی کی گاڑی کو شارع اسلام پر رواں دواں رکھا، ان کا طائر علومرتبت فلک کی بلندیوں پرمحو پرواز ر ہا۔ ان کے علم و دانش کا آفتاب و ماہتاب آسمان کی...

تاريخية السنة بين المثبتين والنافين

A group of contemporary rationalists have repeatedly maintained that the rulings derived from the Sunnah have a historical framework that does not transcend them. After being proved, they must remain locked in the time in which they were said, and we are not obliged to follow them. The prophetic interpretation of the Qur'anic text is not the only interpretation, Is one possible form of interpretation. The rationalists market some evidence of this, including: copies, reasons for descent and causes of roses, and the language of some Koranic verses. In this research we will discuss the issue of this issue, and the statements of the parties and their evidence.

Ardl Model As a Remedy for Spurious Regression: Problems, Performance and Prospects

The most important feature that directed to the development of new time series econometrics was the spurious regression. It is a phenomenon known to econometricians since the times of Yule (1926) who attributed this problem to missing variable. A spurious regression occurs when two independent series come up with significant regression results. For a long time, missing variables were considered as root cause of spurious regression. However, Granger and Newbold (1974) challenged this wisdom and presented unit root as one of the causes of spurious regression. The extensive literature considers the nonstationarity as the only cause of spurious regression. The researchers frequently employed unit root and co-integration procedures for the treatment of spurious regression in case of nonstationarity but these procedures are equally unreliable because of uncertainty about various specification decisions like choice of the deterministic part, structural breaks, choice of autoregressive, lag length and distribution of error term. On the other hand Granger et al. (2001) show that unit root is not the only reason for spurious regression. They show the possibility of spurious regression in stationary time series. Whereas unit root and cointegration are unable to deal with this problem because they deal only nonstationary series. Such amount of conventional econometric literature is inadequate to deal with the problem of spurious regression in stationary time series. The objective of this study is to provide an alternative solution of spurious regression for both stationary and nonstationary time series. So, this study makes two contributions in this particular setup. First, spurious regression occurs due to missing variable and can be avoided by including missing lag values. Therefore, an alternative way to look at the problem of spurious regression takes us back to the missing variable (lag values) which further leads to ARDL model. Second, it significantly reduces the probability of spurious regression in both stationary and nonstationary time series case. This study mainly focusing on Monte Carlo simulations and real data is also used for performance comparison of ARDL model and conventional procedures. Our results indicate that conventional methods are significantly suffering in size and there is power problems but the performance of ARDL in both cases is far better than conventional methods. ARDL model significantly reduced the probability of spurious regression in stationary and nonstationary time series case.
Asian Research Index Whatsapp Chanel
Asian Research Index Whatsapp Chanel

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