scholarly journals The joint distribution of the running maximum and its location of D-valued Markov processes

1995 ◽  
Vol 32 (3) ◽  
pp. 842-845 ◽  
Author(s):  
Dietmar Ferger
Keyword(s):  
Markov Processes ◽  
Joint Distribution ◽  
Running Maximum

A note on functions of Markov processes with an application to a sequence of χ2 statistics

1973 ◽  
Vol 10 (4) ◽  
pp. 895-900
Author(s):  
Murray A. Cameron
Keyword(s):  
Markov Process ◽  
Markov Processes ◽  
Joint Distribution ◽  
Sufficient Condition ◽  
Simple Derivation ◽  
Reverse Process

A sufficient condition for a function of a Markov process to be Markovian is obtained by considering a reverse process of the original Markov process. An application of this result provides a simple derivation of the joint distribution of a sequence of Pearson χ2 statistics previously obtained by Zaharov, Sarmanov and Sevast'ianov (1969).

On occupation times for quasi-Markov processes

1981 ◽  
Vol 18 (01) ◽  
pp. 297-301 ◽  
Author(s):  
Lennart Bondesson
Keyword(s):  
Markov Process ◽  
Laplace Transform ◽  
Markov Processes ◽  
Joint Distribution ◽  
Stieltjes Transform ◽  
Occupation Times ◽  
The Laplace Transform ◽  
The Times

In this note the joint distribution for the times in an interval [0, t] spent in the states 1, 2, ···, N in a standard quasi-Markov process of order N is considered. An expression for the Laplace transform with respect to t of the Laplace–Stieltjes transform of this joint distribution is derived.

Some results about Markov processes on subsets of the state space

1976 ◽  
Vol 8 (3) ◽  
pp. 517-530 ◽  
Author(s):  
Cristina Gzyl
Keyword(s):  
State Space ◽  
Markov Processes ◽  
Joint Distribution ◽  
Regular Point ◽  
The State ◽  
Hunt Process ◽  
Perfect Subset ◽  
Image Position

Kingman [5] proved a formula that expresses the joint distribution of the processes where b is a regular point in the state space of a Hunt process. We give an extension of this formula, as well as several interesting facts related to it, for the case when Φ is any finely perfect subset of the state space. We also establish some connections between this result and results on last-exit decompositions.

Some results about Markov processes on subsets of the state space

1976 ◽  
Vol 8 (03) ◽  
pp. 517-530 ◽  
Author(s):  
Cristina Gzyl
Keyword(s):  
State Space ◽  
Markov Processes ◽  
Joint Distribution ◽  
Regular Point ◽  
The State ◽  
Hunt Process ◽  
Perfect Subset ◽  
Image Position

Kingman [5] proved a formula that expresses the joint distribution of the processes where b is a regular point in the state space of a Hunt process. We give an extension of this formula, as well as several interesting facts related to it, for the case when Φ is any finely perfect subset of the state space. We also establish some connections between this result and results on last-exit decompositions.

On occupation times for quasi-Markov processes

1981 ◽  
Vol 18 (1) ◽  
pp. 297-301 ◽  
Author(s):  
Lennart Bondesson
Keyword(s):  
Markov Process ◽  
Laplace Transform ◽  
Markov Processes ◽  
Joint Distribution ◽  
Stieltjes Transform ◽  
Occupation Times ◽  
The Laplace Transform ◽  
The Times

In this note the joint distribution for the times in an interval [0, t] spent in the states 1, 2, ···, N in a standard quasi-Markov process of order N is considered. An expression for the Laplace transform with respect to t of the Laplace–Stieltjes transform of this joint distribution is derived.

A note on functions of Markov processes with an application to a sequence of χ2 statistics

1973 ◽  
Vol 10 (04) ◽  
pp. 895-900
Author(s):  
Murray A. Cameron
Keyword(s):  
Markov Process ◽  
Markov Processes ◽  
Joint Distribution ◽  
Sufficient Condition ◽  
Simple Derivation ◽  
Reverse Process

A sufficient condition for a function of a Markov process to be Markovian is obtained by considering a reverse process of the original Markov process. An application of this result provides a simple derivation of the joint distribution of a sequence of Pearson χ 2 statistics previously obtained by Zaharov, Sarmanov and Sevast'ianov (1969).

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