Print  Close

Ancestral Inference for Branching Process in Random Environments

Abstract Number:

2504 

Submission Type:

Contributed Abstract 

Contributed Abstract Type:

Paper 

Participants:

Xiaoran Jiang (1), Anand Vidyashankar (1)

Institutions:

(1) George Mason University, Fairfax, VA

Co-Author:

Anand Vidyashankar  
George Mason University

First Author:

Xiaoran Jiang  
George Mason University

Presenting Author:

Xiaoran Jiang  
N/A

Abstract Text:

Ancestral inference for Branching processes in random environments (BPRE) is concerned with the inference regarding the parameters of the ancestor distribution generating the process. In this presentation, we describe a new generalized method of moments methodology for inference using replicated BPRE data. Even though the evolution of the process strongly depends on the offspring means of various generations, we establish that the joint limiting distribution of the ancestor and the offspring estimators mean, under appropriate centering and scaling, decouple and converge to independent normal random variables when the ratio of the number of generations to the logarithm of the number of replicates converge to zero. We also provide estimators for the limiting variance and illustrate our results using numerical experiments and data from Polymerase Chain Reaction (PCR) experiments.

Keywords:

BPRE|Ancestral Inference|Joint CLT|PCR| |

Sponsors:

IMS

Tracks:

Statistical Methodology

Can this be considered for alternate subtype?

No

Are you interested in volunteering to serve as a session chair?

No

I have read and understand that JSM participants must abide by the Participant Guidelines.

Yes

I understand that JSM participants must register and pay the appropriate registration fee by June 1, 2024. The registration fee is non-refundable.

I understand