In surveys, one may face the problem of influential units at the estimation stage.
A unit is said to be influential if its inclusion or exclusion from the sample has a
drastic impact on the estimates. This is a common situation in business surveys
as the distribution of economic variables tends to be highly skewed. We study and
examine some commonly used estimators and predictors of a population total and
propose a robust estimator and predictor based on an adaptive tuning constant. The
proposed tuning constant is based on the concept of conditional bias of a unit, which
is a measure of influence. We present the results of a simulation study that compares
the performance of several estimators and predictors in terms of bias and efficiency.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/45218 |
| Date | 02 August 2023 |
| Creators | Teng, Yizhen |
| Contributors | Haziza, David |
| Publisher | Université d'Ottawa / University of Ottawa |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
| Rights | CC0 1.0 Universal, http://creativecommons.org/publicdomain/zero/1.0/ |
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