Estimation in second order branching processes with application to swine flu data. Issue 4 (16th February 2016)
- Record Type:
- Journal Article
- Title:
- Estimation in second order branching processes with application to swine flu data. Issue 4 (16th February 2016)
- Main Title:
- Estimation in second order branching processes with application to swine flu data
- Authors:
- Kashikar, Akanksha S.
Deshmukh, S. R. - Abstract:
- Abstract: This paper discusses inferential issues related to estimation of offspring mean and variance in a second order branching process, when both the offspring distributions are assumed to have identical mean and variance. Estimating equation approach is used to find the estimator of the offspring mean and the fact that a second order branching process model can be modeled as an autoregressive process is utilized to obtain the estimator of the offspring variance. Both the estimators are shown to be consistent and asymptotically normal. The second order branching process model is applied to H1N1 data for Pune, India, and Mexico and is found to be a suitable model. The estimates obtained from this model are used to compute the proportion of vaccination required for elimination of the disease.
- Is Part Of:
- Communications in statistics. Volume 45:Issue 4(2016)
- Journal:
- Communications in statistics
- Issue:
- Volume 45:Issue 4(2016)
- Issue Display:
- Volume 45, Issue 4 (2016)
- Year:
- 2016
- Volume:
- 45
- Issue:
- 4
- Issue Sort Value:
- 2016-0045-0004-0000
- Page Start:
- 1031
- Page End:
- 1046
- Publication Date:
- 2016-02-16
- Subjects:
- Confidence intervals -- Estimating functions -- Least square estimation -- Second order branching process.
60J80
Mathematical statistics -- Periodicals
Mathematics
Statistics
519.2 - Journal URLs:
- http://www.tandfonline.com/ ↗
- DOI:
- 10.1080/03610926.2013.853796 ↗
- Languages:
- English
- ISSNs:
- 0361-0926
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3363.432000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 322.xml