کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7408681 1481454 2012 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Kernel density estimation for time series data
موضوعات مرتبط
علوم انسانی و اجتماعی مدیریت، کسب و کار و حسابداری کسب و کار و مدیریت بین المللی
پیش نمایش صفحه اول مقاله
Kernel density estimation for time series data
چکیده انگلیسی
A time-varying probability density function, or the corresponding cumulative distribution function, may be estimated nonparametrically by using a kernel and weighting the observations using schemes derived from time series modelling. The parameters, including the bandwidth, may be estimated by maximum likelihood or cross-validation. Diagnostic checks may be carried out directly on residuals given by the predictive cumulative distribution function. Since tracking the distribution is only viable if it changes relatively slowly, the technique may need to be combined with a filter for scale and/or location. The methods are applied to data on the NASDAQ index and the Hong Kong and Korean stock market indices.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: International Journal of Forecasting - Volume 28, Issue 1, January–March 2012, Pages 3-14
نویسندگان
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