Description Usage Arguments Value References Examples

View source: R/smoothedLasso.r

Auxiliary function which returns the objective, penalty, and dependence structure among regression coefficients of the Lasso for polygenic risk scores (prs).

1 | ```
prsLasso(X, y, s, lambda)
``` |

`X` |
The design matrix. |

`y` |
The response vector. |

`s` |
The shrinkage parameter used to regularize the design matrix. |

`lambda` |
The regularization parameter of the prs Lasso. |

A list with six functions, precisely the objective *u*, penalty *v*, and dependence structure *w*, as well as their derivatives *du*, *dv*, and *dw*.

Mak, T.S., Porsch, R.M., Choi, S.W., Zhou, X., and Sham, P.C. (2017). Polygenic scores via penalized regression on summary statistics. Genet Epidemiol, 41(6):469-480.

Mak, T.S. and Porsch, R.M. (2020). lassosum: LASSO with summary statistics and a reference panel. R package version 0.4.5.

Hahn, G., Lutz, S., Laha, N., and Lange, C. (2020). A framework to efficiently smooth L1 penalties for linear regression. bioRxiv:2020.09.17.301788.

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