An algorithm for modelling a normal distribution
β Scribed by I.G. Dyad'kin
- Publisher
- Elsevier Science
- Year
- 1985
- Weight
- 281 KB
- Volume
- 25
- Category
- Article
- ISSN
- 0041-5553
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
The ability to formally analyse and represent semantic relations of terms is a major challenge for many areas of computing science and an intriguing problem for other sciences. In applications of evidence theory to, for instance, information retrieval, the problem of analysis and representation beco
We present an algorithm for the construction of a normal basis of a Galois extension of degree n in characteristic 0. The algorithm requires O(n 4 ) multiplications in the ground field. It is based on representation theory but does not require the knowledge of representation theoretical data (like c
The Normal-Inverse Gaussian distribution arises as a Normal variance-mean mixture with an Inverse Gaussian mixing distribution. This article deals with Maximum Likelihood estimation of the parameters of the Normal-Inverse Gaussian distribution. Due to the complexity of the likelihood, direct maximiz
We propose in this paper a new normal form for dynamical systems or vector fields which improves the classical normal forms in the sense that it is a further reduction of the classical normal forms. We give an algorithm for an effective computation of these normal forms. Our approach is rational in