Cargando…
Outlier Detection Method in Linear Regression Based on Sum of Arithmetic Progression
We introduce a new nonparametric outlier detection method for linear series, which requires no missing or removed data imputation. For an arithmetic progression (a series without outliers) with n elements, the ratio (R) of the sum of the minimum and the maximum elements and the sum of all elements i...
Autores principales: | Adikaram, K. K. L. B., Hussein, M. A., Effenberger, M., Becker, T. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4121229/ https://www.ncbi.nlm.nih.gov/pubmed/25121139 http://dx.doi.org/10.1155/2014/821623 |
Ejemplares similares
-
Universal Linear Fit Identification: A Method Independent of Data, Outliers and Noise Distribution Model and Free of Missing or Removed Data Imputation
por: Adikaram, K. K. L. B., et al.
Publicado: (2015) -
A method for detecting outliers in linear-circular non-parametric regression
por: Sert, Sümeyra, et al.
Publicado: (2023) -
On the correlation of multiplicative and the sum of additive arithmetic functions
por: Elliott, PDTA
Publicado: (1994) -
Procedure for Detecting Outliers in a Circular Regression Model
por: Rambli, Adzhar, et al.
Publicado: (2016) -
Find Outliers of Image Edge Consistency by Weighted Local Linear Regression with Equality Constraints †
por: Zhu, Mingzhu, et al.
Publicado: (2021)