## Algorithmic Probability: A Collection of ProblemsThis unique text collects more than 400 problems in combinatorics, derived distributions, discrete and continuous Markov chains, and models requiring a computer experimental approach. The first book to deal with simplified versions of models encountered in the contemporary statistical or engineering literature, Algorithmic Probability emphasizes correct interpretation of numerical results and visualization of the dynamics of stochastic processes. A significant contribution to the field of applied probability, Algorithmic Probability is ideal both as a secondary text in probability courses and as a reference. Engineers and operations analysts seeking solutions to practical problems will find it a valuable resource, as will advanced undergraduate and graduate students in mathematics, statistics, operations research, industrial and electrical engineering, and computer science. |

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absorption algorithm alias method array arrival bability behavior Bernoulli trials bility binomial density busy period calculation choose chosen coefficients coins components compute the probabilities conditional probability Consider convolution corresponding customers defined denote derive Discuss distribution F eigenvalue equal equation Erlang Erlang distribution evaluate Example exponential exponential distribution finite function graph Implement your code independent initial probability vector integers interval irreducible iteration Markov chain Markovian arrival process mean method nonnegative numerical results obtain P//-distribution parameters permutation PH distribution Player plot points Poisson process proba probability density probability distribution procedure quantities random variables random walk recurrence relations representation sample satisfy sequence server Show simulation smallest Solution to Problem steady-state probabilities Stieltjes transform stochastic matrix string subroutine successive tion transition probability matrix trials with probability variance variates Verify wins Write a program Write a subroutine Write an efficient zero

### References to this book

Markov Chains: Models, Algorithms and Applications Wai-Ki Ching,Michael K. Ng No preview available - 2006 |