RobMixReg 0.1.0

• Initial version on CRAN.

RobMixReg 0.2.0

• Update CTLE function to CTLERob function. This new function have one more parameter ‘rlr_method’ which let user choose the robust regression method in ‘lmRob’,‘lmrob’,‘ltsReg’.

• Update class definition of RobMixReg. The new class add one slot which return the posterior probability of the mixture regression.

RobMixReg 0.2.1

• Our paper published on arxiv, please cite us. For more detail of the proposed method, please refer to DESCRIPTION file.

RobMixReg 1.0.0

• Add method mixtureReg which let user run the mixture regression model flexibility by fixing the specific coefficient (slpoe value).

• Add method Regression Based Suspace Learning (RBSL) that enable to fitting the mixture model for high dimension variable. The implementation is ‘CSMR’ function.

• Add new wrapper function to deal with following four scenarios:

1. robust regression: one regression line and outliers.

2. flexible mixture regression: two regression lines without outliers. The flexible means that the coefficient of the regression line can be declare by the user.

3. robust mixture regression: two regression lines with outliers. The algorithm to solve this challenge is Component-wise Adaptive Trimming (CAT). the implementation is ‘CTLERob’ function. The details of the algorithm please refer our paper.

4. supervised subspace clustering: clustering heterogeneity objects into subgroup and selecting contributed attributes simultaneously. The algorithm to solve this challenge is RBSL. The details of the algorithm please refer our paper.

• Add plot module for the above four scenarios.

• Add two real dataset: Breast cancer multi-omic data and Two genes cytokine response data. The detail and example refer to package manual and vignette.

RobMixReg 1.1.0

• add several wrapper function

• add model selection method

• update vignette