Description Usage Arguments Value

View source: R/squeezeVarRob.R View source: R/squeezeVarRob.R

This function squeezes a set of sample variances together by computing empirical Bayes posterior means in a way that is robust against the presence of very small non-integer degrees of freedom values.

1 2 |

`var` |
A numeric vector of independent sample variances. |

`df` |
A numeric vector of degrees of freedom for the sample variances. |

`covariate` |
If |

`robust` |
A logical indicating wheter the estimation of |

`winsor.tail.p` |
A numeric vector of length 1 or 2, giving left and right tail proportions of |

`min_df` |
A numeric value indicating the minimal degrees of freedom that will be taken into account for calculating the prior degrees of freedom and prior variance. |

`k` |
A numeric value indicating that the calculation of the robust squeezed variances should Winsorize at |

A list with components:
`var.post`

A numeric vector of posterior variances.
`var.prior`

The location of prior distribution. A vector if `covariate`

is non-`NULL`

, otherwise a scalar.
`df.prior`

The degrees of freedom of prior distribution. A vector if `robust=TRUE`

, otherwise a scalar.

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