Description Usage Arguments Value Examples

This function is called internally by `lars.c`

to get the quadratic programming fit if the user requests
implementation of the algorithm starting at the smallest lambda
value and proceeding forwards.

1 |

`x` |
independent variable matrix of data to be used in calculating PaC coefficient paths |

`y` |
response vector of data to be used in calculating PaC coefficient paths |

`C.full` |
complete constraint matrix C (with constraints of the form |

`b` |
constraint vector b |

`lambda` |
value of lambda |

`d` |
very small diagonal term to allow for SVD (default 10^-7) |

`beta`

the initial beta vector of coefficients to use for the PaC algorithm

1 2 3 4 | ```
random_data = generate.data(n = 500, p = 20, m = 10)
quad_start = quad.int(random_data$x, random_data$y, random_data$C.full,
random_data$b, lambda = 0.01)
quad_start
``` |

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