Model absorbing chains with flexible transitions and precision. Compare start states, transient paths, and outcomes. Download tables, visualize probabilities, and explain every computed step.
This sample uses four states. States S3 and S4 are absorbing. Start from S1 to see how absorption probabilities are distributed.
| State | To S1 | To S2 | To S3 | To S4 | Type |
|---|---|---|---|---|---|
| S1 | 0.50 | 0.25 | 0.25 | 0.00 | Transient |
| S2 | 0.30 | 0.40 | 0.10 | 0.20 | Transient |
| S3 | 0.00 | 0.00 | 1.00 | 0.00 | Absorbing |
| S4 | 0.00 | 0.00 | 0.00 | 1.00 | Absorbing |
This calculator analyzes an absorbing Markov chain. After arranging states into transient and absorbing groups, the transition matrix is written in canonical form:
P = [ Q R ; 0 I ]
Here, Q contains transient-to-transient probabilities, and R contains transient-to-absorbing probabilities.
The fundamental matrix is:
N = (I - Q)-1
The absorption probability matrix is:
B = N × R
Each row of B gives the probability of ending in each absorbing state when the chain starts from a particular transient state.
Expected steps before absorption are computed with t = N × 1, where 1 is a column vector of ones.
An absorbing state is a state that, once entered, cannot be left. Its transition row has a 1 on its own diagonal entry and 0 everywhere else.
Each row represents all possible next moves from one state. Because one of those moves must occur, the total probability across the row must equal 1.
The fundamental matrix N measures expected visits to transient states before absorption. It is central for computing both absorption probabilities and expected absorption time.
Yes. In that case, the process has already finished. The selected absorbing state gets probability 1, every other absorbing state gets probability 0, and expected steps equal 0.
Validation usually fails when a row does not sum to 1, a probability falls outside 0 to 1, or no absorbing state exists in the matrix.
Yes. Simple fractions such as 1/2, 3/10, and 7/20 are accepted. The calculator converts them into decimals before running the matrix calculations.
That is a standard use case. The result table lists the probability of eventually ending in each absorbing state from the chosen starting state.
It is useful in stochastic processes, game states, reliability models, queueing systems, risk studies, genetics, and any process that eventually terminates in final states.
Important Note: All the Calculators listed in this site are for educational purpose only and we do not guarentee the accuracy of results. Please do consult with other sources as well.