Individual prediction regions for multivariate longitudinal data with small samples

Individual prediction regions for multivariate longitudinal data with small samples.

Follow-up is more and more used in medicine/doping control to identify abnormal results in an individual. Currently, follow-ups are mostly carried out variable by variable using "reference intervals" that contain the values observable in 100(1-α)% of healthy/undoped individuals. Observations of the evolution of the variables over time in a sample of N healthy/undoped individuals, allows these r...

Individual prediction regions for small samples

Follow-up is more and more used in medicine/doping control to identify abnormal results in an individual. Currently, follow-ups are mostly carried out variable by variable using reference intervals" that contain the values observable in 95% of healthy/undoped individuals. Observations of the evolution of the variables over time in a sample of N healthy/undoped individuals, allows these referenc...

Bootstrap prediction regions for multivariate autoregressive processes

Riassunto: L’obiettivo del presente lavoro è studiare il comportamento di una nuova procedura per la determinazione di regioni di previsione per processi autoregressivi multidimensionali. Le regioni di previsione, basate sulla tecnica bootstrap, non fanno affidamento su alcuna assunzione distributiva per i disturbi ed inoltre tengono conto della variabilità derivante dalla necessità di stimare ...

Logistic Regression for Multivariate Longitudinal Ordinal Data

Dynamical Correlation for Multivariate Longitudinal Data

Nonparametric methodology for longitudinal data analysis is becoming increasingly popular. The analysis of multivariate longitudinal data, where data on several time courses are recorded per subject, has received considerably less attention, in spite of its importance for practical data analysis. In particular, there is a need for measures and estimates to capture dependency between the compone...