Selected article for: "seasonality trend and time series"

Author: Pavan Kumar; Ram Kumar Singh; Chintan Nanda; Himangshu Kalita; Shashikanta Patairiya; Yagya Datt Sharma; Meenu Rani; Akshaya Srikanth Bhagavathula
Title: Forecasting COVID-19 impact in India using pandemic waves Nonlinear Growth Models
  • Document date: 2020_4_2
  • ID: b9p5tqhl_13
    Snippet: Time series models provide a different and unique approach to time series forecasting. Basically, for the time series forecast, two approaches are widely used, i.e., exponential smoothing and Time Series Models like ARIMA and Richard's. While exponential smoothing models are based on a description of the trend and seasonality in the data, Time Series, like ARIMA models, aims to describe the autocorrelations in the data......
    Document: Time series models provide a different and unique approach to time series forecasting. Basically, for the time series forecast, two approaches are widely used, i.e., exponential smoothing and Time Series Models like ARIMA and Richard's. While exponential smoothing models are based on a description of the trend and seasonality in the data, Time Series, like ARIMA models, aims to describe the autocorrelations in the data.

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