Add to ORKGThe paper deals with an analysis of how to use certain measures of location in analysis of wages. One of traditional measures of location – the mean should to offer typical value of variable, representing all its values by the best way. Sometimes the mean is located in the tail of the distribution and gives very biased idea about the location of the distribution. The removing of outliers, if any, or using of different measures of location could be useful in these cases. Outliers are characterized and some robust methods of their detecting are described in the paper. Then the trimmed mean and M-estimators are characterized. Computing of one-step M-estimator and modified one-step M-estimator of location is described. The possibilities of usin...
Outlier detection can be seen as a pre-processing step for locating data points in a data sample, wh...
In this article, we present a simple multivariate outlier-detection procedure and a robust estimator...
Determining if a dataset has one or more outliers is a fundamental and challenging problem in statis...
Abstract: Outlier detection concerns discovering some unusual data whose behavior is exceptional com...
WOS: 000391036900006Pre-test estimator has earlier been introduced to estimate the mean of a normal ...
The role and importance of the industrial sector in the economic development necessitate the need to...
The sample mean can have poor efficiency relative to various alternative estimators under arbitraril...
In a data set, an outlier refers to a data point that is considerably different from the others. Det...
Outlier analysis is that the user do depends on the kinds data they have. An outlier is a data value...
The problem of outliers is well-known in statistics: an outlier is a value that is far from the gene...
This thesis reviews various approaches for outlier detection problem. Several popularly used methods...
An outlier is an observation that appears to deviate markedly from other observations in the sample ...
estimator, ratio estimator, influence curve Abstract: The Current Employment Statistics (CES) Survey...
Spatial data are characterized by statistical units, with known geographical positions, on which non...
We introduce asymptotic parameter-free hypothesis tests based on extreme value theory to detect outl...
Outlier detection can be seen as a pre-processing step for locating data points in a data sample, wh...
In this article, we present a simple multivariate outlier-detection procedure and a robust estimator...
Determining if a dataset has one or more outliers is a fundamental and challenging problem in statis...
Abstract: Outlier detection concerns discovering some unusual data whose behavior is exceptional com...
WOS: 000391036900006Pre-test estimator has earlier been introduced to estimate the mean of a normal ...
The role and importance of the industrial sector in the economic development necessitate the need to...
The sample mean can have poor efficiency relative to various alternative estimators under arbitraril...
In a data set, an outlier refers to a data point that is considerably different from the others. Det...
Outlier analysis is that the user do depends on the kinds data they have. An outlier is a data value...
The problem of outliers is well-known in statistics: an outlier is a value that is far from the gene...
This thesis reviews various approaches for outlier detection problem. Several popularly used methods...
An outlier is an observation that appears to deviate markedly from other observations in the sample ...
estimator, ratio estimator, influence curve Abstract: The Current Employment Statistics (CES) Survey...
Spatial data are characterized by statistical units, with known geographical positions, on which non...
We introduce asymptotic parameter-free hypothesis tests based on extreme value theory to detect outl...
Outlier detection can be seen as a pre-processing step for locating data points in a data sample, wh...
In this article, we present a simple multivariate outlier-detection procedure and a robust estimator...
Determining if a dataset has one or more outliers is a fundamental and challenging problem in statis...