Application of one-, three-, and seven-day forecasts during early onset on the COVID-19 epidemic dataset using moving average, autoregressive, autoregressive moving average, autoregressive integrated moving average, and naïve forecasting methods [PDF]
Data in Brief, 2021 The coronavirus disease 2019 (COVID-19) spread rapidly across the world since its appearance in December 2019. This data set creates one-, three-, and seven-day forecasts of the COVID-19 pandemic's cumulative case counts at the county, health district ...
Christopher J. Lynch, Ross Gore
doaj +8 more sources
On continuous-time autoregressive fractionally integrated moving average processes [PDF]
Bernoulli 2009, Vol. 15, No. 1, 178-194, 2009 In this paper, we consider a continuous-time autoregressive fractionally integrated moving average (CARFIMA) model, which is defined as the stationary solution of a stochastic differential equation driven by a standard fractional Brownian motion. Like the discrete-time ARFIMA model, the CARFIMA model is useful for studying time series with short memory,
Henghsiu Tsai
arxiv +8 more sources
Comparative analysis of Gated Recurrent Units (GRU), long Short-Term memory (LSTM) cells, autoregressive Integrated moving average (ARIMA), seasonal autoregressive Integrated moving average (SARIMA) for forecasting COVID-19 trends [PDF]
Alexandria Engineering Journal, 2022 Several machine learning and deep learning models were reported in the literature to forecast COVID-19 but there is no comprehensive report on the comparison between statistical models and deep learning models. The present work reports a comparative time-
K.E. ArunKumar +4 more
doaj +3 more sources
Time series prediction of under-five mortality rates for Nigeria: comparative analysis of artificial neural networks, Holt-Winters exponential smoothing and autoregressive integrated moving average models. [PDF]
BMC Med Res Methodol, 2020 Background Accurate forecasting model for under-five mortality rate (U5MR) is essential for policy actions and planning. While studies have used traditional time series modeling techniques (e.g., autoregressive integrated moving average (ARIMA) and Holt ...
Adeyinka DA, Muhajarine N.
europepmc +4 more sources
Interrupted time series analysis using autoregressive integrated moving average (ARIMA) models: a guide for evaluating large-scale health interventions. [PDF]
BMC Med Res Methodol, 2021 Background Interrupted time series analysis is increasingly used to evaluate the impact of large-scale health interventions. While segmented regression is a common approach, it is not always adequate, especially in the presence of seasonality and ...
Schaffer AL, Dobbins TA, Pearson SA.
europepmc +2 more sources
Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model. [PDF]
Int J Public Health, 2021 Objectives: To predict the number of people with diabetes and estimate the economic burden in China. Methods: Data from natural logarithmic transformation of the number of people with diabetes in China from 2000 to 2018 were selected to fit the ...
Zhu D, Zhou D, Li N, Han B.
europepmc +2 more sources
Indonesian Consumer Price Index Forecasting Using Autoregressive Integrated Moving Average
International Journal of Electronics and Communications System, 2023 The Consumer Price Index is one of the indicators used to confirm financial success in inflation management. This study aims to help determine the CPI prediction value in Indonesia for the next twelve periods in a month using the ARIMA (Autoregressive ...
Shahnaz Salsabila Ishak +6 more
doaj +2 more sources
Forecasting of Milk Production in Northern Thailand Using Seasonal Autoregressive Integrated Moving Average, Error Trend Seasonality, and Hybrid Models. [PDF]
Front Vet Sci, 2021 Milk production in Thailand has increased rapidly, though excess milk supply is one of the major concerns. Forecasting can reveal the important information that can support authorities and stakeholders to establish a plan to compromise the oversupply of ...
Punyapornwithaya V +3 more
europepmc +2 more sources
Frontiers in Applied Mathematics and Statistics, 2022 IntroductionThe price of crude oil as an essential commodity in the world economy shows a pattern and identifies the component factors that influence it in the short and long term.
Dodi Devianto +4 more
doaj +2 more sources
Indian COVID-19 dynamics: Prediction using autoregressive integrated moving average modelling [PDF]
Scripta Medica, 2021 Background: The forecasting of Coronavirus Disease-19 (COVID-19) dynamics is a centrepiece in evidence-based disease management. Numerous approaches that use mathematical modelling have been used to predict the outcome of the pandemic, including data ...
Tak Amit +3 more
doaj +2 more sources