کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
417332 | 681484 | 2008 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
A goodness-of-fit test for normality based on polynomial regression
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
Statistical models are often based on normal distributions and procedures for testing such distributional assumption are needed. Many goodness-of-fit tests are available. However, most of them are quite insensitive in detecting non-normality when the alternative distribution is symmetric. On the other hand all the procedures are quite powerful against skewed alternatives. A new test for normality based on a polynomial regression is presented. It is very effective in detecting non-normality when the alternative distribution is symmetric. A comparison between well known tests and this new procedure is performed by simulation study. Other properties are also investigated.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 52, Issue 4, 10 January 2008, Pages 2185–2198
Journal: Computational Statistics & Data Analysis - Volume 52, Issue 4, 10 January 2008, Pages 2185–2198
نویسندگان
Daniele Coin,