Results 61 to 70 of about 6,621,438 (152)

Local Whittle estimation in time‐varying long memory series

Journal of Time Series Analysis, Volume 46, Issue 4, Page 647-673, July 2025.
The memory parameter is usually assumed to be constant in traditional long memory time series. We relax this restriction by considering the memory a time‐varying function that depends on a finite number of parameters. A time‐varying Local Whittle estimator of these parameters, and hence of the memory function, is proposed.
Josu Arteche, Luis F. Martins
wiley   +1 more source

Improved Trend Analysis With EOFs and Application to Warming of Polar Regions

International Journal of Climatology, Volume 45, Issue 7, 15 June 2025.
Introducing a variation of EOF analysis, we obtain an insignificant Antarctic trend between 1979 and 2023 of (0.13 ± 0.17) K/decade. The first principal component completely captures the trend for land regions of the order of the size of most countries.
Ewan T. Phillips, Holger Kantz
wiley   +1 more source

Forecasting pastoralist red meat production trajectories in a fragile and climate-vulnerable state: a comparative evaluation of classical, state-space, long-memory, and neural network models in Somalia

Pastoralism
BackgroundThe national economy of Somalia is significantly reliant on the production of pastoralist red meat, a sector that is increasingly debilitated by severe and recurrent climate-related shocks. Accurate forecasting of supply trajectories is crucial
Abdirisak Osman Bade, Dahir Muse Shire, Saleban Mohamed Hassan, Abdisalam Hassan Muse   +3 more
doaj   +1 more source

Identifying influential individuals and predicting future demand of chronic kidney disease patients

Decision Sciences, Volume 56, Issue 2, Page 123-143, April 2025.
ABSTRACT To ensure high service quality, managers need to personalize treatment options and meet their customer demands. Our research is motivated by the need to better anticipate and prepare for that. We develop a generalizable framework that is the first to address two healthcare risk management goals: (1) identifying high risk and stable‐demand ...
Zlatana D. Nenova, Valerie L. Bartelt
wiley   +1 more source

Autoregression-Based Estimators for ARFIMA Models [PDF]

, 2001
Nous décrivons une méthode d'estimation pour les paramètres des modèles ARFIMA stationnaires ou non-stationnaires, basée sur l'approximation auto-régressive.
Galbraith, John, Zinde-Walsh, Victoria
core   +1 more source

Wavelet Covariance Matrix Structure and Bayesian-Wavelet Estimation of Autoregressive Process Parameters with Long-Term Memory

پژوهش‌های ریاضی, 2020
Introduction The data obtained from observing a phenomenon over time is very common. One of the most popular models in time series and signal processing is the Autoregressive moving average model (ARMA).
Mahmod Afshari, Saeed Tahmasbi, Shabnam Shadman   +2 more
doaj  

A COMPARATIVE STUDY BETWEEN UNIVARIATE AND BIVARIATE TIME SERIES MODELS FOR CRUDE PALM OIL INDUSTRY IN PENINSULAR MALAYSIA

Malaysian Journal of Computing, 2020
The main purpose of this study is to compare the performances of univariate and bivariate models on four-time series variables of the crude palm oil industry in Peninsular Malaysia.
Pauline Jin Wee Mah, Nur Nadhirah Nanyan
doaj   +1 more source

Heart rate variability analysis in healthy subjects, patients suffering from congestive heart failure and heart transplanted patients

Motricidade, 2013
This study aimed to find parameters to characterize heart rate variability (HRV) and discriminate healthy subjects and patients with heart diseases. The parameters used for discrimination characterize the different components of HRV memory (short and ...
Argentina Leite, Maria Eduarda Silva, Ana Paula Rocha   +2 more
doaj   +1 more source

Prediction of maintenance workforce efficiency using neural networks, fuzzy inference system and autoregressive fractionally integrated moving average for a process industry

Vietnam Journal of Science, Technology and Engineering
This study establishes the efficiency of the maintenance workforce in a process plant, utilising combined models, including artificial neural networks (ANN)-weighted aggregated sum product assessment (WASPAS) and ANN-fuzzy inference system (FIS)-WASPAS.
Sunday Ayoola Oke, Desmond Eseoghene Ighravwe   +1 more
doaj  

تحسين التنبؤ باستخدام الجمع بين نماذج ARFIMA و GARCH (دراسة تطبيقية) Improving Forecasting Using a Combination of ARFIMA and GARCH Models ( An Applied Study). [PDF]

المجلة العلمية للدراسات والبحوث المالية والتجارية
تهدف هذه الدراسة إلى بناء نموذج هجين يجمع بين نماذج ARFIMA و GARCH لتوقع أسعار الذهب الشهرية خلال الفترة من 2010 إلى 2025، نظرًا لما تتسم به هذه السلسلة من تقلبات وتعقيد، أظهرت اختبارات ADF وPP   أن السلسلة غير ساكنة، كما أكدت تحليلات الذاكرة الطويلة مثل
فاطمة الزهراء ابراهيم ابراهيم اللاوندي, أمال عبد الغني مبارك, محمد إبراهيم محمد   +2 more
doaj   +1 more source