2 options
Multiple imputation for estimation of AR(1) process parameters.
- Format:
- Book
- Thesis/Dissertation
- Author/Creator:
- Diaz-Tena, Nuria.
- Language:
- English
- Subjects (All):
- Statistics.
- 0463.
- Penn dissertations--Statistics.
- Statistics--Penn dissertations.
- Penn dissertations--Managerial science and applied economics.
- Managerial science and applied economics--Penn dissertations.
- Local Subjects:
- Penn dissertations--Statistics.
- Statistics--Penn dissertations.
- Penn dissertations--Managerial science and applied economics.
- Managerial science and applied economics--Penn dissertations.
- 0463.
- Physical Description:
- 109 pages
- Contained In:
- Dissertation Abstracts International 62-05B.
- System Details:
- Mode of access: World Wide Web.
- text file
- Summary:
- We present a method for estimation of the parameters of an AR(1) process with missing data. This method uses multiple imputation to permit estimation of the parameters of the process and their variances as accurately as possible. I find that there is an inevitable obstacle for a good imputation method for autoregressive processes. This obstacle arises because of the correlation in the data, which causes measurement error bias.
- Notes:
- Thesis (Ph.D. in Statistics) -- University of Pennsylvania, 2001.
- Source: Dissertation Abstracts International, Volume: 62-05, Section: B, page: 2371.
- Supervisor: Paul Shaman.
- Local Notes:
- School code: 0175.
- ISBN:
- 9780493254579
- Access Restriction:
- Restricted for use by site license.
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