Abstract Models characterized by autoregressive structure and random coefficients are
powerful tools for the analysis of high-frequency, high-dimensional and volatile time series …

This article considers a first order continuous time vector autoregression with random
coefficients. We discuss some difficulties that arise when the exact discrete analogue is used …

Estimating functionshave been shown to be convenient to study inference for non linear time
series models. Recently, Thavaneswaran et al. used combined estimating functions to study …

時間序列分析是一套動態數據處理的統計方法. 基於隨機過程及數理統計理論,
分析變數的產生與變數間之動態關係, 進而能檢定經濟理論或對變數進行預測 …

The periodic autoregressive model with first-order random coefficients RCPAR (1) is one of
the models that is based on imposing the best description of seasonal variation and …

The first-order random coefficient periodic autoregressive model RCPAR (1) was introduced
by researchers (Frances and Paap, 2011), due to its importance in the field of seasonal time …

يعد انموذج الانحدار الذاتي الدوري بمعاملات عشوائية من الرتبة الاولى RCPAR (1) من النماذج التي
تبنى على فرض افضل وصف للتباين الموسمي والفروق من خلال السماح للمعلمات في الانحدار …‎

تم تقديم انموذج الانحدار الذاتي الدوري ذو المعامل العشوائي من الرتبة الاولى RCPAR (1) من قبل
الباحثين (Frances and Paap, 2011), وذلك لاهميته في مجال تطبيقات السلاسل الزمنية الموسمية …‎

This paper considers an application of estimating functions (EF) in the estimation of
regression models with heteroscedastic errors. It is shown that the class of estimators using …

In statistics the term longitudinal data refers to “data collected at a sequence of time points
for each of a sample of individuals"[227]. Thus a longitudinal study design involves multiple …