Time Series SARIMA Modelling and Forecasting of Monthly Rainfall and Temperature in the South Asian Countries

State of the art in total pulse production in major states of India using ARIMA techniques

“…In non-stationary data, ARMA( p , q ) model is known as the ARIMA( p , d , q ) models if the d-order difference operation is performed to make the data stationary. In the kind of equations in the ARIMA ( p, d, q ) models, p represents the degree of the AR model, q represents the degree of the MA model, and d represents the number of differences needed to stabilize the data ( Yonar et al, 2020 ; Ray et al, 2021 ; Mishra et al, 2021a , Mishra et al, 2021b ).…”

Predicting Diabetes and Estimating Its Economic Burden in China Using Autoregressive Integrated Moving Average Model

“…The third step was the model testing and diagnosis. The white noise test of residuals was performed using the Box.test function [ 11 ]. The Lagrange multiplier (LM) test of residuals was performed using the ArchTest function [ 21 ].…”

“…The ARIMA (p, d, q) model was applied to nonstationary series, so we checked whether the series was nonstationary. We chose the Augmented Dickey Fuller (ADF) test [11] to check if the series is stationary, and to determine the value of the model order d. The second step was the model order determination. Thus, we used the autocorrelation function (ACF) graph and partial autocorrelation function (PACF) graph to select the p and q.…”

“…The ARIMA model was used to predict Alzheimer’s disease mortality in the United States from 2019 to 2023 [ 10 ]. In addition, ARIMA model has a wide range of applications in fields such as meteorology [ 11 ], economics [ 12 ] and agriculture [ 13 ].…”

Comparing LSTM and GRU Models to Predict the Condition of a Pulp Paper Press

“…Traditional forecasting algorithms have relied more on time series models, such as exponential smoothing [7] and seasonal autoregressive integrated moving average (SARIMA) [8][9][10].…”