posturo

This dataset represents a subset from the posturographic data collected in Leitner et al. (sensory organisation test SOT).

datasets

This package contains two main functions: gpava() for
        solving general isotone regression problem using the
        pool-adjacent-violators algorithm (PAVA). activeSet() provides
        a framework of active set methods for isotone optimization
        problems with arbitrary order restrictions. Various types of
        loss functions are pre-spcified.

Jan Leeuw

isotone

Active set and generalized PAVA for isotone optimization

posturo function

A data frame with 50 subjects, age as predictor and 3 repeated SOT measures as responses.

posturo: Repeated posturographic measures

Description

Usage

Arguments

format

References

Examples