1. Anscombe and Guttman (1960) define an outlier an “observation which is suspected of being partially or wholly irrelevant because it is not generated by ...

This paper presents a study of the mean-shift method for detecting outliers in asymmetric normal regression models. Analytical solutions for the estimators of ...

Jun 23, 2016 · In this paper we propose a HNLM considering skew scale mixtures of normal (SSMN) distributions, which allows fitting asymmetric and heavy-tailed ...

Oct 22, 2024 · This paper presents a study of the mean-shift method for the detection of outliers in regression models under skew scale-mixtures of normal ...

1. Normal distribution is used in various fields of applications due to its mathematical tractability and various attractive properties.

Dec 13, 2023 · Therefore, when the distribution of data is skewed to the left, the mean is often less than the median. When the distribution is skewed to the ...

For distributions that have outliers or are skewed, the median is often the preferred measure of central tendency because the median is more resistant to ...

Dec 16, 2014 · For skewed distributions (Exponential, Poisson, Geometric, etc) is the best way to detect an outlier by analyzing a transform of the original function?

Data is skewed when the curve appears distorted to the left or right in a statistical distribution. In a normal distribution, the graph appears symmetrical, ...

This paper developed a new family of finite mixture models where the components follow the class of contaminated mean-mixture distributions, called the CMMN- ...