کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
7543071 | 1489160 | 2011 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Generating low-discrepancy sequences from the normal distribution: Box-Muller or inverse transform?
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موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
Quasi-Monte Carlo simulation is a popular numerical method in applications, in particular, economics and finance. Since the normal distribution occurs frequently in economic and financial modeling, one often needs a method to transform low-discrepancy sequences from the uniform distribution to the normal distribution. Two well known methods used with pseudorandom numbers are the Box-Muller and the inverse transformation methods. Some researchers and financial engineers have claimed that it is incorrect to use the Box-Muller method with low-discrepancy sequences, and instead, the inverse transformation method should be used. In this paper we prove that the Box-Muller method can be used with low-discrepancy sequences, and discuss when its use could actually be advantageous. We also present numerical results that compare Box-Muller and inverse transformation methods.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mathematical and Computer Modelling - Volume 53, Issues 5â6, March 2011, Pages 1268-1281
Journal: Mathematical and Computer Modelling - Volume 53, Issues 5â6, March 2011, Pages 1268-1281
نویسندگان
Giray Ãkten, Ahmet Göncü,