traj 3.0.0

• Substantial modifications to the measures.

• The clustering step now relies of a version of spectral clustering

• The main function are trajMeasures (computes the measures) and trajClusters (finds the clusters), with trajReduce (finds a representative subset of measures) being accessory.

• The plotting functions that trajClusters can be passed into are now plot, scatterplots and CVIplot.

traj 2.2.1

• Added a new measure, “m5: slope of linear model”.

• Spit the “plot” function into three: plot, plot.scatter and plot.crit.

• Improved the presentation of the scatter plots.

• Made Step1Measures more lenient with how the input data is formatted.

traj 2.2.0

• Added k-medoids as the default clustering algorithm.
• Added the Calinski-Harabasz index as the default criterion for determining the optimal number of clusters.

traj 2.1.0

• Makes substantial changes to the list of measures.
• In trajdata, the group of size 30 is made up of quadratic (instead of linear) curves.
• Introduces the vignette “Using the traj package”.

traj 2.0.1

• Fixes minor bugs and improves presentation.

traj 2.0.0

• Changes the way the measures are computed in order to be better suited to missing values and unequally spaced observation times.
• Allows for better control over the choice of a “midpoint”.
• Implements a capping procedure to automatically handle outliers. Measures of the form 0/0 are set to 1.
• Fixes an important bug in the implementation of step 2.
• The criterion of Tibshirani et al. based on the GAP statistic is the new default for choosing the number of clusters.
• Allows more control over the parameters of kmeans.
• The outputs of summary, print and plot are more detailed.