Heuristically deciding between normal and skew normal distributions for describing the data on a response variable and an explanatory variable
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Publication:2320894
DOI10.1080/15598608.2013.823581zbMath1423.62063OpenAlexW2057403326MaRDI QIDQ2320894
Publication date: 27 August 2019
Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/15598608.2013.823581
likelihoodmodel selectionlinear approximationnormal distributionmaximum likelihoodshape parameterskew normal distributionMill's ratio
Cites Work
- On the approximation of the tail probability of the scalar skew-normal distribution
- A note on bias reduction of maximum likelihood estimates for the scalar skew \(t\) distribution
- Discriminating between Weibull and generalized exponential distributions
- The nontruncated marginal of a truncated bivariate normal distribution
- The epsilon-skew-normal distribution for analyzing near-normal data
- Bias prevention of maximum likelihood estimates for scalar skew normal and skew \(t\) distribu\-tions
- Discriminating between the Weibull and log-normal distributions
- Probability of correct selection of weibull versus gamma based on livelihood ratio
- Problems of inference for Azzalini's skewnormal distribution
- Flexible Class of Skew-Symmetric Distributions
- Bias reduction of maximum likelihood estimates
- Likelihood Ratio Test for Discrimination between Two Models with Unknown Location and Scale Parameters
- Discrimination between the Log-Normal and the Weibull Distributions
- Maximum Likelihood Estimation of Misspecified Models
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