Effect of sampling on the estimation of drift parameter of continuous time AR(1) processes
Radhendushka Srivastava, Ping Li
TL;DR
This paper investigates how stochastic sampling influences the accuracy of estimating the drift parameter in continuous-time AR(1) processes, focusing on the impact of sampling frequency constraints.
Contribution
It introduces a distribution-free moment estimator for the drift and analyzes how minimum separation constraints between samples affect estimation accuracy.
Findings
Sampling constraints significantly impact drift estimation accuracy.
The proposed estimator remains robust under stochastic sampling.
Sampling frequency influences the bias and variance of the estimator.
Abstract
We study the effect of stochastic sampling on the estimation of the drift parameter of continuous time AR(1) process. A natural distribution free moment estimator is considered for the drift based on stochastically observed time points. The effect of the constraint of the minimum separation between successive samples on the estimation of the drift is studied.
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Taxonomy
TopicsDistributed Sensor Networks and Detection Algorithms · Target Tracking and Data Fusion in Sensor Networks · Advanced Statistical Process Monitoring