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Global, Parameterwise and Joint Shrinkage Factor Estimation
Journal of Statistical Software, 2016 The predictive value of a statistical model can often be improved by applying shrinkage methods. This can be achieved, e.g., by regularized regression or empirical Bayes approaches. Various types of shrinkage factors can also be estimated after a maximum
Daniela Dunkler +2 more
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A Class of Shrinkage Estimators
Journal of the Royal Statistical Society Series B: Statistical Methodology, 1978 Summary In this paper we define a class of shrinkage estimators, all of whose members have a mean square error matrix which is less than that of the ordinary least squares estimator by a positive semidefinite matrix if (β-b *)T X T X (β-b *) ≤ σ2.
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Interval shrinkage estimation of two-parameter exponential distribution with random censored data [PDF]
Journal of Mahani Mathematical ResearchThe use of the two-parameter exponential distribution model in fitting survival and reliability analysis data in the presence of censored random data has recently attracted the attention of a large number of authors.
Ali Soori +4 more
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From Minimax Shrinkage Estimation to Minimax Shrinkage Prediction
Statistical Science, 2012 Published in at http://dx.doi.org/10.1214/11-STS383 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)
George, Edward I, Liang, Feng, Xu, Xinyi
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A nonparametric mean-variance smoothing method to assess Arabidopsis cold stress transcriptional regulator CBF2 overexpression microarray data. [PDF]
PLoS ONE, 2011 Microarray is a powerful tool for genome-wide gene expression analysis. In microarray expression data, often mean and variance have certain relationships.
Pingsha Hu, Tapabrata Maiti
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Shrinkage Estimation of Linear Regression Models with GARCH Errors [PDF]
Journal of Statistical Theory and Applications (JSTA), 2016 This paper introduces shrinkage estimators for the parameter vector of a linear regression model with con- ditionally heteroscedastic errors such as the class of generalized autoregressive conditional heteroscedastic (GARCH) errors when some of the ...
S. Hossain, M. Ghahramani
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Austrian Journal of Statistics, 2015 This paper derives Bayes shrinkage estimator of Rayleigh parameter and its associated risk based on conjugate prior under the assumption of general entropy loss function for progressive type-II censored data. Risk function of maximum likelihood estimate,
Sanku Dey +2 more
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CoRR, 2019 Networks are a natural representation of complex systems across the sciences, and higher-order dependencies are central to the understanding and modeling of these systems. However, in many practical applications such as online social networks, networks are massive, dynamic, and naturally streaming, where pairwise interactions among vertices become ...
Nesreen K. Ahmed, Nick Duffield
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Estimation of Dispersed Glaciation Shrinkage Under Climate Change
Geography, Environment, Sustainability, 2019 We propose a new method of estimating the shrinkage of glaciers over a wide area under conditions of changed climate. The method can be also used to quantitatively estimate the presence of glaciers under past climatic conditions, in mountainous areas ...
Gleb E. Glazirin, Eleonora R. Semakova
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