Description Usage Arguments Details Value Author(s) See Also Examples

Provides list of covariates and their estimates of parametric AFT model with smooth time functions, whose p value is less than chosen value (by default p=1 that is all chosen covariates come in result). Using AFT model for univariate in high dimensional data without MCMC.

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`m` |
Starting column number of covariates of study in high dimensional entered data. |

`n` |
Ending column number of covariates of study in high dimensional entered data. |

`STime` |
name of survival time in data. |

`Event` |
name of event in data. 0 is for censored and 1 for occurrence of event. |

`p` |
p-value, to make restriction for selection of covariates, default value is 1. |

`data` |
High dimensional gene expression data that contains event status, survival time and and set of covariates. |

Survival time T for covariate x, is modelled as AFT model using

*S(T|x)=S_0(T\exp(-η(x;β)))*

and baseline survival function is modelled as

*S_0(T)=\exp(-\exp(η_0(log(T);β_0)))*

Where *η* and *η* are linear predictor.

Matrix that contains survival information of selected covariates(selected from chosen columns whose p value is <= p) on AFT model. Result shows together for all covariates chosen from column m to n.

Atanu Bhattacharjee, Gajendra Kumar Vishwakarma and Pragya Kumari

wbysuni,wbysmv, rglaft

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