Method of Moments Estimators and Multu-step MLE for Poisson Processes

06/17/2018
by   Ali S. Dabye, et al.
0

We introduce two types of estimators of the finite-dimensional parameters in the case of observations of inhomogeneous Poisson processes. These are the estimators of the method of moments and multi-step MLE. It is shown that the estimators of the method of moments are consistent and asymptotically normal and the multi-step MLE are consistent and asymptotically efficient. The construction of multi-step MLE-process is done in two steps. First we construct a consistent estimator by the observations on some learning interval and then this estimator is used for construction of one-step and two-step MLEs. The main advantage of the proposed approach is its computational simplicity.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/17/2018

Poisson Source Localization on the Plane. Smooth Case

We consider the problem of localization of Poisson source by the observa...
research
10/15/2020

On Multi-step Estimation of Delay for SDE

We consider the problem of delay estimation by the observations of the s...
research
04/14/2016

Consistently Estimating Markov Chains with Noisy Aggregate Data

We address the problem of estimating the parameters of a time-homogeneou...
research
12/26/2022

Spectral and post-spectral estimators for grouped panel data models

In this paper, we develop spectral and post-spectral estimators for grou...
research
04/11/2022

Consistent Estimators for Nonlinear Vessel Models

In this work, the issue of obtaining consistent parameter estimators for...
research
09/10/2020

A note on estimation of α-stable CARMA processes sampled at low frequencies

In this paper, we investigate estimators for symmetric α-stable CARMA pr...
research
07/15/2019

An efficient estimator of the parameters of the Generalized Lambda Distribution

Estimation of the four generalized lambda distribution parameters is not...

Please sign up or login with your details

Forgot password? Click here to reset