outlier


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outlier

 [out´li-er]
an observation so distant from the central mass of the data that it noticeably influences results and must be carefully checked to ensure it is not an error.

out·li·er

(owt'lē-ĕr),
An observation that differs so widely from all others in a set as to justify the conclusion that a gross error has occurred or that it comes from a different population.

outlier

Any value outside of an expected range.

outlier

Managed care A Pt who falls outside of the norm–ie, who has an extremely long length of hospital stay or has incurred extraordinarily high costs. See Extreme outlier, High mortality outlier.

out·li·er

(owt'lī-ĕr)
1. Deviant values or figures that are obviously from a different population than those from the rest of the sample.
2. Additions to an estimated cost of delivered services when exceeding a fixed loss threshold.
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References in periodicals archive ?
The most common outlier treatments in finance are winsorizing, trimming, and dropping (referred to hereafter as WTD).
Identifying and treating outliers in finance
As "Outliers" argues, this constant churning--this trespassing of the borders of high and low, this teetering between the unknown and the famous--is essential to the dynamism of American art itself.
"Outliers and American Vanguard Art": NATIONAL GALLERY OF ART, WASHINGTON, DC
"Joint Estimation of Model Parameters and Outlier Effects in Time Series." Journal of the American Statistical Association, 88, 1993, 284-97.
DOES THE GREAT RECESSION IMPLY THE END OF THE GREAT MODERATION? INTERNATIONAL EVIDENCE
Some outliers may position themselves on the fringe, seeking to gain reputations as innovators.
Scholar Outliers and the State of Scholarship
Before applying the LOF algorithm, it is necessary to specify two parameters: the number of closest neighbours k and the threshold value, above which it is considered that the record is outlier. When choosing the number of closest neighbours, it is recommended that k value would be equal to square root of all data, used for the model training.
Application of Local Outlier Factor Algorithm to Detect Anomalies in Computer Network
For the point outliers, results from outlier method #1 (Standard Deviation), #2 (Quartile), and # 3 (Grubbs' Test) are 7, 17, 12 outliers respectively.
Characteristics and Causes of Outliers in Inverse Modeling of Residential Building Energy Use Data
From a practical point of view, it is well known that Pearson's correlation is not resistant to outliers and thus choosing weights in (2) based on this correlation will cause uncertain and deceptive results.
Robust Group Identification and Variable Selection in Regression
The relative prediction error term indicates whether the point is an outlier. The larger value of [r.sub.t] means the current point is more suspicious to be an outlier.
Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory
Velleman, "BACON: blocked adaptive computationally efficient outlier nominators," Computational Statistics and Data Analysis, vol.
Robust Nonlinear Partial Least Squares Regression Using the BACON Algorithm
Ruiz-Gazen, Outlier Detection Using Invariant Coordinate Selection.
Network Intrusion Detection with Threat Agent Profiling
Unlike other outlier detect method (such as the traditional AR model detection method), the outliers detect method proposed in this paper does not need to set the detection threshold.
Online Outlier Detection for Time-varying Time Series on Improved ARHMM in Geological Mineral Grade Analysis Process
It works on the premise that many outliers are unaware they are an outlier, no one wants to be an outlier, and confidential, collegial education and peer mentoring within a medical specialty society can reduce unnecessary variations in care.
Finally, a reproducible quality measure for Mohs

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