Markov for Continuous Distributions

• Family of PDF
• If a Markov Chain with state set S, matrix M is executed m times . The transition probabilities transmit between states and then, $P(X_{n+m}=s_j|X_n=s_i)=M^m(i,j)$
• where $M^m=M\cdot M\cdot M\dots \cdot M$ (m times)
• To get the PDF $g^{n+1}(x)={\int }_{{\mathbb{R}}^k}T(x|y)g^n(y)dy$
• Invariant Distribution