Changes in version 1.1.0 (2020-08-05) - add several wrapper function - add model selection method - update vignette Changes in version 1.0.0 (2020-06-08) - 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. Changes in version 0.2.1 (2020-05-26) - Our paper published on arxiv, please cite us. For more detail of the proposed method, please refer to DESCRIPTION file. Changes in version 0.2.0 (2020-05-11) - 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. Changes in version 0.1.0 (2020-03-25) - Initial version on CRAN.