How to Compute the Sum in the Stationary Distribution of a Markov Chain?

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SUMMARY

This discussion focuses on computing the sum in the stationary distribution of a Markov chain defined by the equation ##p_n=\frac{a}{nb+c}p_{n-1}##, where ##a, b,## and ##c## are positive constants. The key formula derived is ##p_n=p_0\prod_{i=1}^n\frac{a}{ib+c}##, leading to the normalization condition ##1=p_0\sum_{n=0}^\infty\prod_{i=1}^n\frac{a}{ib+c}##. The challenge presented is to simplify the product term into manageable components for further analysis.

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TaPaKaH
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Suppose we have a Markov chain with stationary distributions ##p_n=\frac{a}{nb+c}p_{n-1}## for ##n\in\mathbb{N}## where ##a,b## and ##c## are some positive constants.
It follows that ##p_n=p_0\prod_{i=1}^n\frac{a}{ib+c}##. Normalisation yields ##1=p_0\sum_{n=0}^\infty\prod_{i=1}^n\frac{a}{ib+c}## so ##p_0=\left(\sum_{n=0}^\infty\prod_{i=1}^n\frac{a}{ib+c}\right)^{-1}##.

Question: how can one compute the sum in the brackets?
 
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TaPaKaH said:
Suppose we have a Markov chain with stationary distributions ##p_n=\frac{a}{nb+c}p_{n-1}## for ##n\in\mathbb{N}## where ##a,b## and ##c## are some positive constants.
It follows that ##p_n=p_0\prod_{i=1}^n\frac{a}{ib+c}##. Normalisation yields ##1=p_0\sum_{n=0}^\infty\prod_{i=1}^n\frac{a}{ib+c}## so ##p_0=\left(\sum_{n=0}^\infty\prod_{i=1}^n\frac{a}{ib+c}\right)^{-1}##.

Question: how can one compute the sum in the brackets?
Well, let's think about this. What can we do to simplify $$\prod_{1\leq i\leq n}\frac{a}{bi+c}$$ into "workable" terms? Can you give us an attempt?
 

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