Examples of Markov Chains - A Very Simple Weather Model

A Very Simple Weather Model

The probabilities of weather conditions (modeled as either rainy or sunny), given the weather on the preceding day, can be represented by a transition matrix:

 P = \begin{bmatrix} 0.9 & 0.1 \\ 0.5 & 0.5 \end{bmatrix}

The matrix P represents the weather model in which a sunny day is 90% likely to be followed by another sunny day, and a rainy day is 50% likely to be followed by another rainy day. The columns can be labelled "sunny" and "rainy", and the rows can be labelled in the same order.

(P)i j is the probability that, if a given day is of type i, it will be followed by a day of type j.

Notice that the rows of P sum to 1: this is because P is a stochastic matrix.

Read more about this topic:  Examples Of Markov Chains

Famous quotes containing the words simple, weather and/or model:

    On a level plain, simple mounds look like hills; and the insipid flatness of our present bourgeoisie is to be measured by the altitude of its “great intellects.”
    Karl Marx (1818–1883)

    When the weather suits you not,
    Try smiling;
    When your coffee isn’t hot,
    Try smiling;
    Unknown. Try Smiling (l. 1–4)

    When Titian was mixing brown madder,
    His model was posed up a ladder.
    Said Titian, “That position
    Calls for coition,”
    So he lept up the ladder and had her.
    Anonymous.