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

Calculates the coefficients for the iterative bias reduction smoothers. This function is not intended to be used directly.

1 | ```
betaA(n, eigenvaluesA, tPADmdemiY, DdemiPA, ddlmini, k, index0)
``` |

`n` |
The number of observations. |

`eigenvaluesA` |
Vector of the eigenvalues of the
symmetric matrix |

`tPADmdemiY` |
The transpose of the matrix of eigen vectors of the
symmetric matrix |

`DdemiPA` |
The square root of the diagonal matrix |

`ddlmini` |
The number of eigenvalues (numerically) equals to 1. |

`k` |
A scalar which gives the number of iterations. |

`index0` |
The index of the first eigen values of |

See the reference for detailed explanation of *A* and
*D* and the meaning of coefficients.

Returns the vector of coefficients (of length *n*, the number of observations.)

Pierre-Andre Cornillon, Nicolas Hengartner and Eric Matzner-Lober.

Cornillon, P.-A.; Hengartner, N.; Jegou, N. and Matzner-Lober, E. (2012)
Iterative bias reduction: a comparative study.
*Statistics and Computing*, *23*, 777-791.

Cornillon, P.-A.; Hengartner, N. and Matzner-Lober, E. (2013)
Recursive bias estimation for multivariate regression smoothers Recursive
bias estimation for multivariate regression smoothers.
*ESAIM: Probability and Statistics*, *18*, 483-502.

Cornillon, P.-A.; Hengartner, N. and Matzner-Lober, E. (2017)
Iterative Bias Reduction Multivariate Smoothing in R: The ibr Package.
*Journal of Statistical Software*, *77*, 1–26.

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