Description Usage Arguments Value Examples
Model-based clustering with two clusters for one-dimensional hour of the day data. Expectation maximization algorithm is implemented that takes into account that the hour of the day data are circular, i.e. 00:00 is the same as 24:00. The circularity is being handled by defining a truncated normal distribution.
1 | timeclust(x)
|
x |
a vector with the hour of the day data. |
loglik |
Final log-likelihood estimate of the EM algorithm. |
parameters |
Parameters inferred by the algorithm:
|
classification |
Classification of the datapoints to the clusters. |
iter |
Number of iterations of the algorithm. |
1 2 3 4 5 6 7 8 | |
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