Isotonic regression is a well-known nonparametric tool for fitting monotonic models and has been studied from both theoretical and practical aspects for several decades, with applications in psychology, medicine, biology, among others. However, it has enjoyed only limited interest in recent years in the context of modern statistical applications. We believe the two major reasons for this limite...

Recursive partitioning is embedded into the general and well-established class of parametric models that can be fitted using M-type estimators (including maximum likelihood). An algorithm for model-based recursive partitioning is suggested for which the basic steps are: (1) fit a parametric model to a data set, (2) test for parameter instability over a set of partitioning variables, (3) if ther...

An algorithm was derived for using morphometric data to classify bowhead whales into three age brackets: over 90 years (‘very old’); 60–90 (‘old’); and under 60 (‘younger’). Recursive partitioning applied a subset of the from post mortem examinations. This consisted with higher quality scores either estimated ages or characteristics very old animals such as: near-maximum body length baleen leng...

BACKGROUND Breast cancer is the main cause of women cancer mortality. Therefore, precise prediction of patients' risk level is the major concern in therapeutic strategies. Although statistical learning algorithms are high quality risk prediction methods, but usually their better prediction quality leads to more loss of interpretability. Therefore, the aim of this study is to compare 'Model-Base...

Among the multitude of learning algorithms that can be employed for deriving quantitative structure-activity relationships, regression trees have the advantage of being able to handle large data sets, dynamically perform the key feature selection, and yield readily interpretable models. A conventional method of building a regression tree model is recursive partitioning, a fast greedy algorithm ...