Monte Carlo errors with less errors
β Scribed by Ulli Wolff
- Book ID
- 108314152
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 352 KB
- Volume
- 156
- Category
- Article
- ISSN
- 0010-4655
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
For estimating the effects of a number of systematic errors on a data sample, one can generate Monte Carlo (MC) runs with systematic parameters varied and examine the change in the desired observed result. Two methods are often used. In the unisim method, 1 the systematic parameters are varied one a
Some statistical models defined in terms of a generating stochastic mechanism have intractable distribution theory, which renders parameter estimation difficult. However, a Monte Carlo estimate of the log-likelihood surface for such a model can be obtained via computation of nonparametric density es