JANOŠOVÁ, Markéta and Stanislav KATINA. Methods of Estimating Parameters of Skewed or Truncated Normal Distribution in the Presence of Observations Outside of Measurable Range. In Olomoucian Days of Applied Mathematics 2023. 2023.
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Basic information
Original name Methods of Estimating Parameters of Skewed or Truncated Normal Distribution in the Presence of Observations Outside of Measurable Range
Authors JANOŠOVÁ, Markéta and Stanislav KATINA.
Edition Olomoucian Days of Applied Mathematics 2023, 2023.
Other information
Original language English
Type of outcome Conference abstract
Field of Study 10103 Statistics and probability
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
Organization unit Faculty of Science
Keywords in English measurable range; parameter estimation; limit of detection
Tags International impact
Changed by Changed by: Mgr. Markéta Janošová, učo 394407. Changed: 21/6/2023 12:13.
Abstract
Every laboratory equipment has limits to what it can accurately measure. Generally, for every laboratory apparatus three types of limits should be defined – limit of blank (LoB), limit of detection (LoD) and limit of quantitation (LoQ). If an observation falls outside of the measurable range, there is an issue of estimating parameters of the distribution. In this contribution we look at four different methods applied to samples generated from skewed and truncated normal distributions – ignoring censored observations, replacing censored observations, using a truncated version of target distribution, and using target distribution with censored observations. To compare these methods we designed a simulation study, where generated samples were truncated from the left at selected quantiles. Parameters’ estimates were then compared to the original values. Simulation study was run separately on skewed normal distribution and truncated normal distribution. Based on the results we created recommendations for practical data analysis.
Links
MUNI/A/1132/2022, interní kód MUName: Matematické a statistické modelování 7
Investor: Masaryk University
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