Forecasted dengue incidence in Iloilo using SARIMA, identifying multi‑year outbreak cycles for public health planning
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Updated
Dec 10, 2025 - R
Forecasted dengue incidence in Iloilo using SARIMA, identifying multi‑year outbreak cycles for public health planning
Time series analysis of Uzbekistan's monthly inflation (2010–2024) using R. Includes detrending, stationarity testing, ACF/PACF analysis, SARIMA modeling, and 1-step ahead forecasting. Dataset sourced from the National Statistics Committee of Uzbekistan.
Time series forecasting of daily COVID-19 testing in Iceland using R. Models compared include ETS, SARIMA, and Auto ARIMA with cross-country validation on UAE data.
Analysis of global sunspot numbers spanning from 1700 to 2023, featuring forecasts derived using a SARIMA model
Beer national sales forecasting
Time Series Forecasting RShiny dashboard
Here is a time series analysis using R and Arima models to predict air traffic for Hong Kong Airport.
Time series modelling with extended regression SARIMA models
Time series project on Paris Airport - ENSAE ParisTech
Time series analysis | seasonal and unseasonal series
Repositório do projeto de conclusão de curso, orientado pelo professor Glauco Gonçalves, do curso de Bacharelado em Sistemas de Informação da Universidade Federal Rural de Pernambuco. Semestre 2019.2
Application of real-time visualization and forecasting of COVID-19 build on R and shiny
The project involved developing an ARIMA model to forecast the monthly Australian gas production level for the next 12 months.
Trabalho realizado para aprovação na disciplina de Análise de Séries Temporais. Foi realizado a análise e modelagem da serie temporal da entrega de fertilizantes ao mercado brasileiro em mil toneladas no período mensal de janeiro de 1998 até abril de 2020 (Fonte: ANDA)
total raw governmental industry employment data from January 1 1939 to October 30 2019. Time Series analysis to forecast employment from October 2019-October 2020.
Market Share Prediction of Top 3 Mobile Vendors using Time Series Analysis
Identified the most appropriate Time-Series method to forecast drought in African countries, acting as a critical early warning for drought managements
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