Description: Fitting tree-structured varying coefficient models (Berger et al. (2018), <doi:10.1007/s11222-018-9804-8>). Simultaneous detection of covariates with varying coefficients and effect modifiers that induce varying coefficients if they are present.

Description: Fitting tree-structured varying coefficient models (Berger et al. (2019), <doi:10.1007/s11222-018-9804-8>). Simultaneous detection of covariates with varying coefficients and effect modifiers that induce varying coefficients if they are present.

Author: Pablo Montero Manso, José Antonio Vilar
Description: This package contains a set of measures of dissimilarity
between time series to perform time series clustering. Metrics
based on raw data, on generating models and on the forecast
behavior are implemented. Some additional utilities related to
time series clustering are also provided, such as clustering
algorithms and cluster evaluation metrics.
Depends: R (>= 2.14.0), nlme,locpol, KernSmooth, dtw, longitudinalData,

Description: This package contains a set of measures of dissimilarity between time series to perform time series clustering. Metrics based on raw data, on generating models and on the forecast behavior are implemented. Some additional utilities related to time series clustering are also provided, such as clustering algorithms and cluster evaluation metrics.
Depends: R (>= 2.14.0), locpol, KernSmooth, dtw, longitudinalData,

Depends: R (>= 3.0.1), wmtsa, pdc, cluster
Imports: locpol, KernSmooth, dtw, longitudinalData

Description: A set of measures of dissimilarity between time series to perform time series clustering. Metrics based on raw data, on generating models and on the forecast behavior are implemented. Some additional utilities related to time series clustering are also provided, such as clustering algorithms and cluster evaluation metrics.

Authors@R: c(person("Pablo", "Montero Manso", role= c("cre"), email="pmontm@gmail.com"),
Imports: locpol, KernSmooth, dtw, longitudinalData, forecast
Maintainer: Pablo Montero Manso <pmontm@gmail.com>