In a time series or otgerr form of sequential data, the transition probability measures the conditional probability of moving from one state to another. For example, if it is sunny today, we may know from historical data that the probabilty it will also be sunny tomorrow is 0.4. Tranistion prpbabolities can also be caclculated based on more than one past state, for example, if the last two days were dry, how likely isto alos be dry tomorrow. Transition probabilities can be sued to create a Markov model of the process.
Used in Chap. 14: pages 208, 209