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Register a new userUse Akaike (AIC) and Schwartz (SC) information criterions in the differentiation between nonlinear growth models of different fish species
استخدام معياري المعلومات أكايك (AIC) و شوارتز (SC) في المفاضلة بين نماذج النمو غير الخطية للأنواع السمكية المختلفة
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Aِl-Baath University ورقة بحثية
Publication date
2018
fields
Veterinary Medicine
and research's language is
العربية
Authors
نادر اسكندر حموي( باحث )
Created by
Shamra Editor
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يعد معيار المعلومات أكايك (AIC) مقياساً للجودة النسبية للنماذج الإحصائية لمجموعة معينة من البيانات. كما يعد معيار المعلومات شوارتز (SC) مقياساً للمساعدة في الاختيار بين النماذج المرشحة.
The Akaike information criterion (AIC) is a measure of the relative quality of statistical models for a given set of data. The Schwarz Criterion (SC) is a measure to help in the selection between candidate models.
References used
Aho, K., Derryberry, D., Peterson, T. 2014 Model selection for ecologists: the worldviews of AIC and BIC, Ecology, 95: 631–636
Akaike, H. 1981. Likelihood of a model and information criteria. J. Econom, 16, 3–14
Burnham, P., Anderson, R. 2002 – Model Selection and Multimodel Inference: A Practical Information-theoretic Approach, 2nd ed. Springer, New York
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نظم المعلومات الجغرافية
(Geographic Information System (GIS
التحليل المكاني
Kriging
نموذج الارتفاع الرقمية
المسافة الموزونة المعكوسة
الاشتقاق المكاني
المنهجية المنتظمة
المنهجية المتواترة
التحليل الجيو إحصائي
السطح المستمر
التخمين الإحصائي
التحليل ثلاثي الأبعاد
الشبكة المثلثاتية غير المنتظمة
خطوط التسوية
(Digital Elevation Model (DEM
Contour Lines
(Triangulated Irregular Network (TIN
3D Analyst
Continuous Surface
المزيد..
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