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

/out·li·er/ (out´li-er) an observation so distant from the central mass of the data that it noticeably influences results.

outlier

1 (in managed care) a case in which costs exceed the allowable amount for the specific diagnosis or treatment. The outlier amount is typically specified in advance in the contract between the provider and payer.
2 (in research) an observation that differs from all others, suggesting that a gross error has occurred in sampling, measurement, or analysis.

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.

outlier

an extremely high or low value lying beyond the range of the bulk of the data.
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References in periodicals archive ?
Results show that our RKF based on residual vectors can effectively reduce the effects of a single outlier.
A new Robust Kalman filtering algorithm of unequal precision observations based on residual vectors in static precise point positioning
We do not require any assumptions on the distribution of the outlier points; our simulations in the next section consider a uniform distribution and a half-normal.
Outliers in data envelopment analysis
If we had only conducted one round of outlier removal, we would have identified 4 outliers, instead of 9.
Iterative outlier removal: a method for identifying outliers in laboratory recalibration studies
The Outlier deals quite well with rough handling, and the headband is flexible to make sure it fits on your head well.
Creative Outlier review: Wireless audio with a few compromises
In accordance with current method, the results described in Table 1 for small sample sizes n = 20 and n = 50 indicate that, given the application in unanalyzed samples, increase in outlier percentage ([gamma]) reduced probability in favor of [H.
Principal components in the discrimination of outliers: a study in simulation sample data corrected by Pearson's and Yates's chi-square distance/Componentes principais na discriminacao de outliers: estudo de simulacao em dados amostrais corrigidos pelas distancias qui-quadrado de Pearson's and Yates
i] exceeding the cutoff point of value [+ or -]3 is suspected as outlier.
Identification of Multiple Outliers in a Generalized Linear Model with Continuous Variables
Outlier detection method based on distance is proposed by Knorr and Raymond (Knorr & Ng, 1999; Edwin & Raymond, 1998), an new detected method based on density is suggested by Ramaswamy et al.
Online Outlier Detection for Time-varying Time Series on Improved ARHMM in Geological Mineral Grade Analysis Process
Of 2,305 physicians billing for Mohs surgery, there were 137 extremely high outliers in at least 1 of 3 years, and 49 persistently high outliers (greater than two standard deviations in all 3 years), who averaged more than 2.
Finally, a reproducible quality measure for Mohs
A Comparative Study for RNN for Outlier Detection in Data Mining".
A privacy preserving data mining approach for handling data with outliers
Outlier conducts weekly mastermind groups, in which an advisory panel of roughly 10 entrepreneurs from all over the world meet through video chat to discuss the good, bad and ugly of starting a business.
Ever Gonzalez: an outlier and innovator in entrepreneurial co-working
Coverage rates for REML and the outlier removal approach were at or above the nominal 0.
Multilevel modeling in the presence of outliers: A comparison of robust estimation methods
In the current academic research, the definition of outlier is not very uniform, and its definition is different with the different application fields.
Multi-dimensional outliers detection method based on RBF neural network model

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