Application of Confidence Regions to Ice Ridge Keel Data Statistical Assessment
Sets of measurements of underwater ridge parts usually contain a limited amount of data. Outcomes need to be made while relying on small sample sizes. In this event, the chance of making inaccurate estimations increases. This paper proposes to use stochastic confidence regions in the estimation of t...
| Published in: | Volume 8: Polar and Arctic Sciences and Technology; Petroleum Technology |
|---|---|
| Main Authors: | , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
American Society of Mechanical Engineers (ASME)
2017
|
| Subjects: | |
| Online Access: | https://cris.vtt.fi/en/publications/bf1a1ded-bb9f-43fb-a41d-ef3041eedb1e https://doi.org/10.1115/OMAE2017-62253 http://www.scopus.com/inward/record.url?scp=85032177496&partnerID=8YFLogxK |
| Summary: | Sets of measurements of underwater ridge parts usually contain a limited amount of data. Outcomes need to be made while relying on small sample sizes. In this event, the chance of making inaccurate estimations increases. This paper proposes to use stochastic confidence regions in the estimation of the unknown parameters of keel depths. A model for a random variable with a lognormal distribution for keel depths is assumed. Regions for the mean and standard deviation of keel depths are obtained from Mood’s and minimum-area confidence regions for parameters of the normally distributed random variable. Conservative safety probability of non-exceeding the critical keel depth in one random interaction of the ridge with structure is estimated. An algorithm for statistically assessment of ice ridge keel data by means of confidence region building is here offered. The assessment of a set of ridge keel depths for the Gulf of Bothnia (Baltic Sea) is performed. |
|---|