Markov process Definition and 16 Threads

Phew! took time to figure this out...i guess there may be a way to use combinations or markov process i do not know... anyway, it was pretty straightforward, we have the ##P_r(w) = \dfrac{n-3}{n}## from box ##X## and this will result in ##P_r(w) = \dfrac{4}{n+1}## in box ##Y##. Together i...

I have already in a previous task shown that A is not irreducible and not regular, which I think is correct. I don't know if I can use that fact here in some way. I guess one way of solving this problem could be to find all eigenvalues, eigenvectors and diagonalize but that is a lot of work and...

Hey! :o We consider the equation \begin{equation*}u_{k+1}=\begin{pmatrix}a & b \\ 1-a & 1-b\end{pmatrix}u_k \ \text{ with } \ u_0=\begin{pmatrix}1 \\1 \end{pmatrix}\end{equation*} For which values of $a$ and $b$ is the above equation a Markov process? Calculate $u_k$ as a function of $a,b$...

Hi everyone! I'm approaching the physics of stochastic processes. In particular I am studying from "Handbook of stochastic processes - Gardiner". This book defines a stationary process like: $$ p(x_1, t_1; x_2, t_2; ...; x_n, t_n) = p(x_1, t_1 + \epsilon; x_2, t_2 + \epsilon; ...; x_n, t_n +...

1. Given a Markov state density function: ## P((\textbf{r}_{n}| \textbf{r}_{n-1})) ## ##P## describes the probability of transitioning from a state at ## \textbf{r}_{n-1}## to a state at ##\textbf{r}_{n} ##. If ## \textbf{r}_{n-1} = \textbf{r}_{n}##, then ##P## describes the probability of...

Homework Statement Calculate the limit $$lim_{s,t→∞} R_X(s, s+t) = lim_{s,t→∞}E(X(s)X(s+t))$$ for a continuous time Markov chain $$(X(t) ; t ≥ 0)$$ with state space S and generator G given by $$S = (0, 1)$$ $$ G= \begin{pmatrix} -\alpha & \alpha \\ \beta & -\beta\...

Homework Statement Let X(t) be a birth-death process with parameters $$\lambda_n = \lambda > 0 , \mu_n = \mu > 0,$$ where $$\lambda > \mu , X(0) = 0$$ Show that the total time T_i spent in state i is $$exp(\lambda−\mu)-distributed$$ 3. Solution I have a hard time understanding this...

Hi I'm using accelerometer & horizontal gyroscope in order to replace GPS. Now, I'want to model the noise with first order markov process, to use it in kalman filter. I recorded measurement on all axes and computed auto-correlation. This picture represents auto-correlation on one of axes...

I have a query on a Random process derived from Markov process. I have stuck in this problem for more than 2 weeks. Let r(t) be a finite-state Markov jump process described by \begin{alignat*}{1} \lim_{dt\rightarrow 0}\frac{Pr\{r(t+dt)=j/r(t)=i\}}{dt} & =q_{ij} \end{alignat*} when i \ne...

Hi all, I know that Brownian process can be shown as Markov process but is the converse possible? I mean can we show that a markov process is a brownian process? Thanks in advance.

I'm trying to learn more about Markov chains and came across the Gibbs sampler x_1{t+1} ~ p(x_1|x_2 = x_2{t},...x_n{t}) x_2{t+1} ~ p(x_2|x_1 = x_1{t+1},x_3 = x_3{t},...,x_n{t}) . . . x_i{t+1} ~ p(x_i|x_1 = x_1{t+1},...,x_(i-1) = x_(i-1){t+1},x_(i+1) = x_(i+1){t},...,x_n{t}) Supposedly...

[FONT=CMR12]It is widely believed that the daily change in currency exchange rates is a random variable with mean 0 and variance v[FONT=CMR12]That is, if [FONT=CMMI12]Y[FONT=CMMI8][FONT=CMMI8]n [FONT=CMR12]represents the exchange rate on the [FONT=CMMI12]n[FONT=CMR12]th day...

Hi, I proved the following statement by induction. Does anyone see any oversights or glaring errors? It is for a class where the homework is assigned but not collected, and I just want to know if I did it right. ThanksQUESTION: Consider the stochastic process \{X_t,\,t=0,1,2,\ldots\} described...

Homework Statement I am in a hurry with the following problem: We have a source that produces binary symbols, 0 and 1. 0 follows a 0 at probability 7/8 1 follows a 1 at probability 1/2 A) Calculate probability of the symbols 0 and 1 to appear. B) Calculate entropy of source. The...

I have a graph where from each node the state can change randomly from one node to some of the other nodes. My task is to estimate how long the state will stay within a subset of all these nodes. Is there a way to characterize the network with some parameters to find the answer (maybe for a...

I've been trying to solve this problem for a week now, but haven't been able to. Basically I need to prove that a certain process satisfies Chapman-Kolmogorov equations, yet it isn't a Markov Process (it doesn't satisfy the Markovian Property). I attached the problem as a .doc below...