Bootstrapping the portmanteau tests in weak auto-regressive moving average models
نویسندگان
چکیده
منابع مشابه
Network Traffic Prediction Model Based on Auto-regressive Moving Average
With the development of Internet and computer science, computer network is changing people’s lives. Meanwhile, Network traffic prediction model itself becomes more and more complex. It is an important research direction to quickly and accurately detect the intrusions or attacks. The performance efficiency of a network intrusion detection system is dominated by pattern matching algorithm. Howeve...
متن کاملA spatiotemporal auto-regressive moving average model for solar radiation
To investigate the variability in energy output from a network of photo-voltaic cells, solar radiation was recorded at ten sites every ten minutes in the Pentland Hills to the south of Edinburgh. We identify spatio-temporal auto-regressive moving average (STARMA) models as the most appropriate to address this problem. Although previously considered computationally prohibitive to work with, we s...
متن کاملA Switchgrass-based Bioethanol Supply Chain Network Design Model under Auto-Regressive Moving Average Demand
Switchgrass is known as one of the best second-generation lignocellulosic biomasses for bioethanol production. Designing efficient switchgrass-based bioethanol supply chain (SBSC) is an essential requirement for commercializing the bioethanol production from switchgrass. This paper presents a mixed integer linear programming (MILP) model to design SBSC in which bioethanol demand is under auto-r...
متن کاملA new hybrid for improvement of auto-regressive integrated moving average models applying particle swarm optimization
A time series forecasting is an active research applied significantly in a variety of economics areas. Over the past three decades an auto-regressive integrated moving average (ARIMA) model, as one of the most important time series models, has been applied in financial markets forecasting. Recent researches in time series forecasting ARIMA models indicate some basic limitations which detract fr...
متن کاملUsing a Fuzzy Auto Regressive Integrated Moving Average Model for Exchange Rate Forecasting
Forecasting models have wide applications in decision making. In the real world, rapid changes normally take place in different areas, specifically in financial markets. Collecting the required data is a main problem for forecasters in such unstable environments. Forecasting methods such as Auto Regressive Integrated Moving Average (ARIMA) models and also Artificial Neural Networks (ANNs) need ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society: Series B (Statistical Methodology)
سال: 2015
ISSN: 1369-7412
DOI: 10.1111/rssb.12112