If I have two independent variables (time series) for two different sources(let's say from Observation and from Model).
Hello Rajkumar,
In Bayesian Statistics, the prior could be classified as informative or non-informative. If you possess real world data, which already shows some trends and you know how the model behaves, you have what is known as an informative prior. In contrast, if you do not have any data, you cannot claim that the prior will behave in a certain manner, it is called a non-informative prior. A non-informative prior is usually assumed as uniformly distributed over the state space of your variables. As you observe more data from your observation time serious, you update your prior using the observation to give you what is known as the posterior probability in the Bayesian terminology.
Thank You Juan and Shameek.
Juan your chapter may help in my work . Actually I want to use this technique for rainfall forecasting for monthly and Seasonally.
Thank you again
- Badges
- Science topic
- Similar topics
- Mathematics
- Statistics