A study is presented for exploring the possibility of applying the source set approach (Djordjilovic V, Chiogna M.(2018)), developed under the assumption of normality, to count data, after data transformation. Some explanations about the source set approach, data trans- formations and the simulation setting are provided. The suggestion is given that the deviance-based or quantile randomized residuals could provide a better basis for data transformation when coupled with source set analysis, along with standard trasformations such as log transformation or square root transformation.
Federico Agostinis, M.C. (2021). Searching for a source of difference in undirected graphical models for count data - an empirical study. PEARSON.
Searching for a source of difference in undirected graphical models for count data - an empirical study
Monica Chiogna;
2021
Abstract
A study is presented for exploring the possibility of applying the source set approach (Djordjilovic V, Chiogna M.(2018)), developed under the assumption of normality, to count data, after data transformation. Some explanations about the source set approach, data trans- formations and the simulation setting are provided. The suggestion is given that the deviance-based or quantile randomized residuals could provide a better basis for data transformation when coupled with source set analysis, along with standard trasformations such as log transformation or square root transformation.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
