Classical and Bayesian Estimations on the Kumaraswamy Distribution using Grouped and Un-grouped Data under Difference Loss Functions

Estimations on the Generalized Exponential Distribution Using Grouped Data

Bayesian density estimation from grouped continuous data

Grouped data occur frequently in practice, either because of limited resolution of instruments, or because data have been summarized in relatively wide bins. A combination of the composite link model with roughness penalties is proposed to estimate smooth densities from such data in a Bayesian framework. A simulation study is used to evaluate the performances of the strategy in the estimation o...

Bayesian Grouped Variable Selection

Traditionally, variable selection in the context of linear regression has been approached using optimization based approaches like the classical Lasso. Such methods provide a sparse point estimate with respect to regression coefficients but are unable to provide more information regarding the distribution of regression coefficients like expectation, variance estimates etc. In the recent years, ...

4. Classical Methods of Analysis of Grouped Data

Model evaluation using grouped or individual data.

Analyzing the data of individuals has several advantages over analyzing the data combined across the individuals (the latter we term group analysis): Grouping can distort the form of data, and different individuals might perform the task using different processes and parameters. These factors notwithstanding, we demonstrate conditions in which group analysis outperforms individual analysis. Suc...