Fitting and Predict Time Series Interactive Laboratory
Interactive laboratory of Time Series based in Box-Jenkins
metodology.
methods, grDevices, graphics, stats, snowfall, MASS

Interactive laboratory of Time Series based in Box-Jenkins
methodology.

methods, grDevices, graphics, stats, MASS

Interactive laboratory of Time Series based in Box-Jenkins methodology.
methods, grDevices, graphics, stats, tools, MASS

Tree-Structured Modelling of Varying Coefficients
Fitting tree-structured varying coefficient models (Berger, M., Tutz, G. & Schmid, M. (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.

Fitting tree-structured varying coefficient models. Simultaneous detection of covariates with varying coefficients and effect modifiers that induce varying coefficients if they are present.

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.

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.

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.
R (>= 2.14.0), nlme,locpol, KernSmooth, dtw, longitudinalData,
wmtsa

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.
R (>= 2.14.0), locpol, KernSmooth, dtw, longitudinalData,
wmtsa