### Abstract

This paper introduces a new Laplace transform inversion method designed specifically for when the target function is a probability distribution function. In particular, we use fixed point theory and Mann type iterative algorithms to provide a means by which to estimate and sample from the target probability distribution.

Language | English (US) |
---|---|

Pages | 439-448 |

Number of pages | 10 |

Journal | Statistics and Computing |

Volume | 27 |

Issue number | 2 |

DOIs | |

State | Published - Mar 1 2017 |

### Fingerprint

### Keywords

- Fixed point solution
- Recursive estimation

### ASJC Scopus subject areas

- Theoretical Computer Science
- Statistics and Probability
- Statistics, Probability and Uncertainty
- Computational Theory and Mathematics

### Cite this

*Statistics and Computing*,

*27*(2), 439-448. DOI: 10.1007/s11222-016-9631-8

**A Laplace transform inversion method for probability distribution functions.** / Walker, Stephen G.

Research output: Research - peer-review › Article

*Statistics and Computing*, vol 27, no. 2, pp. 439-448. DOI: 10.1007/s11222-016-9631-8

}

TY - JOUR

T1 - A Laplace transform inversion method for probability distribution functions

AU - Walker,Stephen G.

PY - 2017/3/1

Y1 - 2017/3/1

N2 - This paper introduces a new Laplace transform inversion method designed specifically for when the target function is a probability distribution function. In particular, we use fixed point theory and Mann type iterative algorithms to provide a means by which to estimate and sample from the target probability distribution.

AB - This paper introduces a new Laplace transform inversion method designed specifically for when the target function is a probability distribution function. In particular, we use fixed point theory and Mann type iterative algorithms to provide a means by which to estimate and sample from the target probability distribution.

KW - Fixed point solution

KW - Recursive estimation

UR - http://www.scopus.com/inward/record.url?scp=84957577242&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84957577242&partnerID=8YFLogxK

U2 - 10.1007/s11222-016-9631-8

DO - 10.1007/s11222-016-9631-8

M3 - Article

VL - 27

SP - 439

EP - 448

JO - Statistics and Computing

T2 - Statistics and Computing

JF - Statistics and Computing

SN - 0960-3174

IS - 2

ER -