Random Motions in Markov and Semi‐Markov Random Environments 1

2021 ◽  
Author(s):  
Anatoliy Pogorui ◽  
Anatoliy Swishchuk ◽  
Ramón M. Rodríguez‐Dagnino
Keyword(s):  
Random Environments ◽  
Markov Random ◽  
Random Motions

Random Motions in Markov and Semi‐Markov Random Environments 2

2021 ◽  
Author(s):  
Anatoliy Pogorui ◽  
Anatoliy Swishchuk ◽  
Ramón M. Rodríguez‐Dagnino
Keyword(s):  
Random Environments ◽  
Markov Random ◽  
Random Motions

Supernovae and interstellar gas dynamics

1967 ◽  
Vol 31 ◽  
pp. 117-119
Author(s):  
F. D. Kahn ◽  
L. Woltjer
Keyword(s):  
Lower Limit ◽  
High Velocity ◽  
Gas Dynamics ◽  
Interstellar Cloud ◽  
Interstellar Gas ◽  
Random Motions ◽  
Relativistic Particles

The efficiency of the transfer of energy from supernovae into interstellar cloud motions is investigated. A lower limit of about 0·002 is obtained, but values near 0·01 are more likely. Taking all uncertainties in the theory and observations into account, the energy per supernova, in the form of relativistic particles or high-velocity matter, needed to maintain the random motions in the interstellar gas is estimated as 1051·4±1ergs.

Sampling from Gaussian Markov random fields conditioned on linear constraints

2008 ◽  
Vol 48 ◽  
pp. 1041 ◽  
Author(s):  
Daniel Peter Simpson ◽  
Ian W. Turner ◽  
A. N. Pettitt
Keyword(s):  
Random Fields ◽  
Markov Random Fields ◽  
Linear Constraints ◽  
Gaussian Markov Random Fields ◽  
Markov Random

On calculating extinction probabilities for branching processes in random environments

1969 ◽  
Vol 6 (03) ◽  
pp. 478-492 ◽  
Author(s):  
William E. Wilkinson
Keyword(s):  
Generating Functions ◽  
Infinite Sequence ◽  
Branching Processes ◽  
Transition Probability ◽  
Transition Probability Matrix ◽  
Random Environments ◽  
Real Numbers ◽  
Discrete Time Markov Chain ◽  
Extinction Probabilities ◽  
Image Position

Consider a discrete time Markov chain {Zn } whose state space is the non-negative integers and whose transition probability matrix ║Pij ║ possesses the representation where {Pr }, r = 1,2,…, is a finite or denumerably infinite sequence of non-negative real numbers satisfying , and , is a corresponding sequence of probability generating functions. It is assumed that Z 0 = k, a finite positive integer.

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