پديد آورنده :
نيكوكار، حامد
عنوان :
آزمون هاي تشخيص ساختار غير خطي در سري هاي زماني
مقطع تحصيلي :
كارشناسي ارشد
گرايش تحصيلي :
رياضي كاربردي
محل تحصيل :
اصفهان: دانشگاه صنعتي اصفهان، دانشكده علوم رياضي
صفحه شمار :
دوازده، [۱۲۰]ص.: مصور، جدول، نمودار
استاد راهنما :
صفيه محمودي
استاد مشاور :
ريحانه ريخته گران
واژه نامه :
انگليسي به فارسي
توصيفگر ها :
سري هاي زماني , مدل خطي و غير خطي , آزمون هاي خطي و غير خطي , سري لكه هاي خورشيدي , سري CREF
استاد داور :
افشين پرورده، مريم كلكين نما
تاريخ ورود اطلاعات :
1396/11/28
چكيده انگليسي :
Nonlinear Diagnostic Tests in Time Series Hamed Nikoukar h nikukar@math iut ac ir 2018 Department of Mathematical Sciences Isfahan University of Technology Isfahan 84156 83111 Iran Supervisor Dr Safieh Mahmoodi mahmoodi@cc iut ac ir Advisor Dr Reyhaneh Rikhtehgaran r rikhtehgaran@cc iut ac ir 2010 MSC 37M10 62F03 Keywords Linear Time series Nonlinear Time series Linear and Nonlinear Tests AbstractSince the earlier contribution of Box and Jenkins 7 identification and estimation of linear modelshave become standard statistical tools for time series analysis By means of a real application it isseen how ARMA forecasts can be improved when nonlinearities are present However it is widelyrecognized that the class of ARMA models may fail to capture fully the dynamics of real phenomenasince these are often characterized by strong nonlinear components For this reason it is importantthat any preliminary analysis or evaluation of model adequacy includes a check on the linearity ofthe generating process One of the challenges of modern time series analysis is to develop tests that are capable of detectingnonlinear structure As Campbell 9 p 467 argue many aspects of economic behavior may not belinear A multitude of statistical procedures designed to test the null hypothesis of linearity againstnonlinear alternatives are available in the literature including general portmanteau tests without aspecifc alternative as well as tests with fully speci ed parametric alternatives During the last few yearsthe interest in modelling nonlinear time series has been growing steadily Tong 10 indicates in hissurvey that the range of areas of application is already vast reaching from ecology and economics tosolar physics In some applications there may be theory available helping the investigator to select thetype of nonlinearity he wants to entertain Unfortunately this is not often the case and a nonlinearmodel is frequently adopted without a solid support of scientific theory Before fitting a nonlinear model to time series data many investigators may want to check if the
استاد راهنما :
صفيه محمودي
استاد مشاور :
ريحانه ريخته گران
استاد داور :
افشين پرورده، مريم كلكين نما
