𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Asymptotic parameter estimation for multivariate point processes

✍ Scribed by V. Kanišauskas

Book ID
105586330
Publisher
Springer
Year
1997
Tongue
English
Weight
551 KB
Volume
37
Category
Article
ISSN
0363-1672

No coin nor oath required. For personal study only.

📜 SIMILAR VOLUMES

Asymptotic theory for multivariate GARCH
Asymptotic theory for multivariate GARCH processes
✍ F. Comte; O. Lieberman 📂 Article 📅 2003 🏛 Elsevier Science 🌐 English ⚖ 272 KB

We provide in this paper asymptotic theory for the multivariate GARCHðp; qÞ process. Strong consistency of the quasi-maximum likelihood estimator (MLE) is established by appealing to conditions given by Jeantheau (Econometric Theory 14 (1998), 70) in conjunction with a result given by Boussama (Ergo

Parameter Estimation and Model Selection
Parameter Estimation and Model Selection for Neyman-Scott Point Processes
✍ Ushio Tanaka; Yosihiko Ogata; Dietrich Stoyan 📂 Article 📅 2008 🏛 John Wiley and Sons 🌐 English ⚖ 362 KB 👁 2 views

## Abstract This paper proposes an approximative method for maximum likelihood estimation of parameters of Neyman‐Scott and similar point processes. It is based on the point pattern resulting from forming all difference points of pairs of points in the window of observation. The intensity function

Optimality Properties of Empirical Estim
Optimality Properties of Empirical Estimators for Multivariate Point Processes
✍ P.E. Greenwood; W. Wefelmeyer 📂 Article 📅 1994 🏛 Elsevier Science 🌐 English ⚖ 531 KB

A multivariate point process is a random jump measure in time and space. Its distribution is determined by the compensator of the jump measure. By an empirical estimator we understand a linear functional of the jump measure. We give conditions for a nonparametric version of local asymptotic normalit