TMixClust: Clusters the time series data in a given number of groups

Description Usage Arguments Value Author(s) References Examples

View source: R/external_TMixClust.R

Description

TMixClust is the central function of the package. It clusters the given time series data into a specified number of clusters.

Usage

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TMixClust(time_series_df, time_points = seq_len(ncol(time_series_df)),
  nb_clusters = 2, em_iter_max = 1000, mc_em_iter_max = 10,
  em_ll_convergence = 0.001)

Arguments

time_series_df

data frame containing the time series. Each row is a time series comprised of the time series name which is also the row name, and the time series values at each time point.

time_points

vector containing numeric values for the time points. Default: seq_len(ncol(time_series_df)).

nb_clusters

desired number of clusters

em_iter_max

maximum number of iterations for the expectation-maximization (EM) algorithm. Default: 1000.

mc_em_iter_max

maximum number of iterations for Monte-Carlo resampling. Default is 100.

em_ll_convergence

convergence threshold for likelihood improvement. Default is 0.001.

Value

list object with the following attributes:

Author(s)

Monica Golumbeanu, monica.golumbeanu@bsse.ethz.ch

References

Golumbeanu M, Desfarges S, Hernandez C, Quadroni M, Rato S, Mohammadi P, Telenti A, Beerenwinkel N, Ciuffi A. (2017) Dynamics of Proteo-Transcriptomic Response to HIV-1 Infection.

Examples

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# Load the toy time series data provided with the TMixClust package
data(toy_data_df)

# Cluster the toy data with default parameters
TMixClust_obj = TMixClust(toy_data_df)

TMixClust documentation built on Nov. 8, 2020, 8:13 p.m.