✦ LIBER ✦

Drawing a random sample from a density selected at random

✍ Scribed by Jeesen Chen; Herman Rubin

Book ID: 103599806
Publisher: Elsevier Science
Year: 1986
Tongue: English
Weight: 831 KB
Volume: 4
Category: Article
ISSN: 0167-9473
DOI: 10.1016/0167-9473(86)90003-4

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Controlled selection a technique in rand

Controlled selection a technique in random sampling

✍ B. V. Sukhatme; M. S. Avadhani 📂 Article 📅 1965 🏛 Springer Japan 🌐 English ⚖ 602 KB

A Bayesian procedure for drawing inferen

A Bayesian procedure for drawing inferences from random data

✍ G. Edwards 📂 Article 📅 1984 🏛 Elsevier Science ⚖ 630 KB

Random field identification from a sampl

Random field identification from a sample: Experimental results

✍ Stanley M. Dunn; Richard L. Keizer; Azriel Rosenfeld 📂 Article 📅 1988 🏛 Elsevier Science 🌐 English ⚖ 383 KB

Generation of a random sample from a mul

Generation of a random sample from a multivariate normal distribution

✍ M.P. Derde; D.L. Massart 📂 Article 📅 1984 🏛 Elsevier Science 🌐 English ⚖ 342 KB

A Linear Algorithm for the Random Sampli

A Linear Algorithm for the Random Sampling from

✍ Olivier Bernardi; Omer Giménez 📂 Article 📅 2010 🏛 Springer 🌐 English ⚖ 597 KB

Random sampling from a truncated bivaria

Random sampling from a truncated bivariate normal distribution

✍ Khalaf E. Ahmad; Nagi S. Abd El-Hakim 📂 Article 📅 1990 🏛 Elsevier Science 🌐 English ⚖ 171 KB

A simple and easily implemented algorithm is presented for obtaining random variables from a truncated standard normal distribution. The algorithm is based on a generalization of Von Neumann's rejection technique. The first-stage sampling in our algorithm is from the truncated logistic distribution.