Autoregressive integrated moving

Môn học "Dự báo trong kinh doanh và kinh tế" với mục tiêu giúp các bạn sinh viên hiểu được những khái niệm cơ bản chuỗi dừng (stationarity) và không dừng (nonstationarity), hiểu được khái niệm kiểm định nghiệm đơn vị (unit root test); Biết được các mô hình giản đơn dùng để dự báo như mô hình san mũ Holt, san mũ Holt-Winters, và mô hình ARIMA (Autoregressive Integrated Moving Average);...Mời các bạn cùng tham khảo!

14p hoangvanlong23 16-07-2024 1 0   Download

Part 1 of ebook "Stochastic processes and calculus: An elementary introduction with applications" provides readers with contents including: Chapter 1 - Introduction; Chapter 2 - Basic concepts from probability theory; Chapter 3 - Autoregressive moving average processes (ARMA); Chapter 4 - Spectra of stationary processes; Chapter 5 - Long memory and fractional integration; Chapter 6 - Processes with autoregressive conditional heteroskedasticity (ARCH);...

163p daonhiennhien 03-07-2024 1 1   Download

This study developed a statistical model for thermal analysis to describe the variation of railway temperature that aids in detecting the potential excessive displacement in the railway efficiently. In particular, the Seasonal autoregressive integrated moving average (SARIMA) model is adopted to learn and recognize the variation patterns of railroad temperature with time.

5p dathienlang1012 03-05-2024 4 0   Download

This study compares the accuracy of two popular time series forecasting models, namely the autoregressive integrated moving average (ARIMA) model and the long short-term memory (LSTM) model, in predicting daily gold prices from 2000 to 2023. The ARIMA model is a traditional approach that relies on past values to forecast future values, while the LSTM model is a deep learning technique that captures long-term dependencies in time series data.

16p dathienlang1012 03-05-2024 0 0   Download

Tác giả nghiên cứu xây dựng và chọn lựa mô hình phù hợp dự báo tỷ giá trung tâm cho loại USD/VND. Phương pháp thực hiện bằng kỹ thuật phân tích chuỗi thời gian Box-Jankins ARIMA (autoregressive integrated moving average) với số liệu tỷ giá trung tâm bình quân thời kỳ (tháng) giai đoạn 2005 đến 2016 (2005M01 – 2016M12).

7p vimarillynhewson 02-01-2024 10 3   Download

Mục tiêu của nghiên cứu này nhằm giới thiệu việc xây dựng mô hình chuỗi thời gian theo phương pháp trung bình trượt tích hợp tự hồi quy (Autoregressive Integrated Moving Average - ARIMA). Với dữ liệu quá khứ trúng tuyển và nhập học từ năm 2007-2022 tại trường đại học Quảng Nam, kết quả của mô hình sẽ dự báo số lượng trúng tuyển và nhập học cho những năm tiếp theo.

8p viengels 25-08-2023 7 2   Download

To compare an autoregressive integrated moving average (ARIMA) model with a model that combines ARIMA with the Elman recurrent neural network (ARIMA-ERNN) in predicting the incidence of pertussis in mainland China. Background: The incidence of pertussis has increased rapidly in mainland China since 2016, making the disease an increasing public health threat.

11p viferrari 28-11-2022 8 2   Download

The study "Application of SARIMA model to forecasting the natural rubber price in the world market" was conducted to develop a forecasting model to predict the price natural rubber in the world market by using the Seasonal Autoregressive Integrated Moving Average (SARIMA).

7p tieuvulinhhoa 22-09-2022 6 3   Download

The Cryptocurrency is growing strongly and widely such as Bitcoin (BTC) and Ethereum (ETH) used in the world, which has attracted wide attention of researchers in recent times. In this work, Autoregressive Integrate Moving Average (ARIMA) model, machine learning algorithms, Support Vector Regression (SVR) will be implemented to predict the closing price of The Cryptocurrency the next day.

7p visherylsandberg 18-05-2022 14 2   Download

Decreasing availability of water and increasing consumption of it in recent years shows water management plans increase its value. Depending on water consumption in the current and previous years, it is important to predict water consumption in the coming years and make plans accordingly. Evaluation of the performance of water use in agriculture, identifying water resources that are most intensively used and prediction of the potential performance in the coming years have become increasingly important.

8p hanthienngao 30-11-2021 10 1   Download

This study compares the price predictions of the Vanguard real estate exchangetraded fund (ETF) (VNQ) using the back propagation neural network (BPNN) and autoregressive integrated moving average (ARIMA) models. The input variables for BPNN include the past 3-day closing prices, daily trading volume, MA5, MA20, the S&P 500 index, the United States (US) dollar index, volatility index, 5-year treasury yields, and 10-year treasury yields. In addition, variable reduction is based on multiple linear regression (MLR).

16p mynguyenha 21-07-2021 18 1   Download

In India, the productivity of various crops is unstable mainly due to climatic factors, price volatility and resource availability. The pre-harvest forecasting of the crop productivity is a major priority to know about the market demand of the crops. The present study focused the ability of pre-harvest forecasting performance of stepwise regression method and the ARIMA method. In stepwise regression method, two approaches were developed namely (1) using week-wise original weather variable and (2) weather indices using correlation coefficient as weight.

10p chauchaungayxua11 23-03-2021 10 1   Download

The current study examined the determinants of electricity consumption and also intends to forecast the electricity consumption in Pakistan. The study has used time series data analysis, applied Johansen Cointegration Test, error correction mechanisms and regression for examining determinants and autoregressive integrated moving average model is used for forecasting. The study has used times series secondary annual data on different variables for the period ranging from 1970 to 2018.

8p nguaconbaynhay10 22-02-2021 17 2   Download

This paper attempts to forecast the economic performance of Bangladesh measured with annual GDP data using an Autoregressive Integrated Moving Average (ARIMA) Model followed by test of goodness of fit using AIC (Akaike Information Criterion) and BIC (Bayesian Information Criterion) index value among six ARIMA models along with several diagnostic tests such as plotting ACF (Autocorrelation Function), PACF (Partial Autocorrelation Function) and performing Unit Root Test of the Residuals estimated by the selected forecasting ARIMA model.

20p nat_qb73 21-02-2021 11 1   Download

This paper examined the monthly modal prices of maize using Autoregressive Integrated Moving Average (ARIMA) models so as to determine the most efficient and adequate model for analyzing the maize monthly modal prices in Telangana.

9p angicungduoc8 07-11-2020 13 1   Download

This study aims to examine the best-fitted model that allows us to forecast FNG prices more accurately in the near future. There are 2842 observed data of daily FNG prices from 2009 to 2019 as the input of study objects. The finding suggests that the first measurement model of ARIMA (1,1,1) does not fit the model as having a non-significant probability value.

7p kethamoi7 15-08-2020 11 1   Download

In this study, total annual exports and imports of the Kingdom of Saudi Arabia are forecasted using Artificial Neural Network (ANN) and Autoregressive Integrated Moving Average (ARIMA) models.

12p tohitohi 22-05-2020 13 0   Download

There are several linear time-series forecasting models available in literature. One of the important and widely used technique for analysis of univariate time-series data is Box Jenkins’ Autoregressive integrated moving average (ARIMA) methodology (Box et al., 2007). Sometimes addition of the other exogenous variables increases the prediction accuracy of ARIMA model (ARIMAX). For this aspect we applied different p and q order ARIMAX model for five nutrient combinations of nitrogen content which is further developed by including organic carbons an input (exogenous) variable.

9p nguaconbaynhay5 16-05-2020 23 0   Download

This model is fitted to time series data both to better understand the data and to forecast future points in the series. Hereby, the methodology is selected by Vietnam's best-fit model ARIMA (2,3,1) and China's best-fit model ARIMA (2,3,5).

10p tozontozon 25-04-2020 6 2   Download

The purpose of this paper is to study the current trend of export of sheep and goat meat from India and forecasting of the same for next five years by using the time series modelling. Four different Autoregressive Integrated Moving Average (ARIMA) models were fitted to annual sheep and goat meat export (quantity) from India using data records from 1990-1991 to 2017-18. Using goodness of fit criteria i.e.

8p trinhthamhodang3 14-02-2020 10 0   Download