O'Reilly logo

Practical Time Series Analysis by Dr. PKS Prakash, Dr. Avishek Pal

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

Understanding Time Series Data

In the previous chapter, we touched upon a general approach of time series analysis which consists of two main steps:

  • Data visualization to check the presence of trend, seasonality, and cyclical patterns
  • Adjustment of trend and seasonality to generate stationary series

Generating stationary data is important for enhancing the time series forecasting model. Deduction of the trend, seasonal, and cyclical components would leave us with irregular fluctuations which cannot be modeled by using only the time index as an explanatory variable. Therefore, in order to further improve forecasting, the irregular fluctuations are assumed to be independent and identically distributed (iid) observations and modeled by a linear ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required