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Missouri State University
Estimation For Simple Linear Regression With Exponentially Distributed Errors
Abstract
dc:description.abstractIn general, the theory developed in the area of linear regression analysis assumes that the error ∊ is normally distributed with mean zero and variance σ². In this thesis, we examine the results when the error ∊ is exponentially distributed with scale parameter ϴ. We derive both the maximum likelihood estimate and the least square estimate and examine their important properties.
Degree
thesis:*- Name thesis:degree_name
- Master of Science in Mathematics
- Level thesis:degree_level
- Masters
- Discipline thesis:degree_discipline
- Mathematics
- Year
- 1992
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Schalda, Anne Therese
- Contributors dc:contributor
-
- George Mathew
Subjects
dc:subject × 1Rights
dc:rights- Statement dc:rights
-
- © Anne Therese Schalda
Identifiers
dc:identifier.*- Repository record dc:identifier
- https://bearworks.missouristate.edu/theses/872
- OAI identifier oai:identifier
- oai:bearworks.missouristate.edu:theses-1873