← Stochastic Processes for Biology

Kolmogorov equations

The Kolmogorov equations describe how CTMC transition probabilities change through continuous time.

Transition matrix

Let \(P(t)\) have entries \(p_{ij}(t)=P(X(t)=j\mid X(0)=i)\), and let \(Q\) be the generator.

Forward equation

\[\frac{dP(t)}{dt}=P(t)Q.\]

Backward equation

\[\frac{dP(t)}{dt}=QP(t).\]

For a finite time-homogeneous CTMC, both are satisfied and \(P(t)=e^{tQ}\).

Probability-vector form

For a row probability vector \(\boldsymbol\pi(t)\),

\[\frac{d\boldsymbol\pi(t)}{dt}=\boldsymbol\pi(t)Q.\]
Key idea. The generator specifies instantaneous rates; the Kolmogorov equations convert those rates into time-dependent state probabilities.