dcem_star_cluster_uv: dcem_star_cluster_uv (univariate data): Part of DCEM package.

Description Usage Arguments Value Author(s) References

View source: R/dcem_star_cluster_uv.R

Description

Implements the EM* algorithm for the univariate data. This function is called by the dcem_star_train routine.

Usage

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2
dcem_star_cluster_uv(data, meu, sigma, prior, num_clusters, num_data,
iteration_count)

Arguments

data

(matrix): The dataset provided by the user.

meu

(vector): The vector containing the initial meu.

sigma

(vector): The vector containing the initial standard deviation.

prior

(vector): The vector containing the initial priors.

num_clusters

(numeric): The number of clusters specified by the user. Default is 2.

num_data

(numeric): number of rows in the dataset (After processing the missing values).

iteration_count

(numeric): The number of iterations for which the algorithm should run. If the convergence is not achieved then the algorithm stops. Default is 100.

Value

A list of objects. This list contains parameters associated with the Gaussian(s) (posterior probabilities, meu, standard-deviation and priors)

  1. (1) Posterior Probabilities: prob A matrix of posterior-probabilities

  2. (2) Meu: meu: It is a vector of meu. Each element of the vector corresponds to one meu.

  3. (3) Sigma: Standard-deviation(s): sigma

    For univariate data: Vector of standard deviation.

  4. (4) Priors: prior: A vector of priors.

  5. (5) Membership: membership: A vector of cluster membership for data.

Author(s)

Parichit Sharma parishar@iu.edu, Hasan Kurban, Mark Jenne, Mehmet Dalkilic

This work is partially supported by NCI Grant 1R01CA213466-01.

References

Hasan Kurban, Mark Jenne, Mehmet M. Dalkilic (2016) <https://doi.org/10.1007/s41060-017-0062-1>.


DCEM documentation built on Aug. 2, 2020, 9:07 a.m.