Description Usage Arguments Value Examples

View source: R/fitting_functions.R

Function to estimate mean and covariance for unknown parameters
*β*.

1 |

`Z` |
list of design points and link function that is an output of
function |

`X` |
model matrix for model formula and design points. The covariates
must correspond to the description of design points in |

`fit.method` |
character, |

`wls.method` |
character giving the numerical solution method: |

list of `mu`

, numeric vector of location parameters for the
normal prior; `Sigma`

, the covariance matrix; and `log.like`

, a
scalar

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ```
X <- matrix(c(1, 1, 0, 1), nrow = 2) # design
Z <- designLink(design = X)
Z <- elicitPt(Z, design.pt = 1,
lower.CI.bound = -1,
median = 0,
upper.CI.bound = 1,
comment = "The first completed elicitation scenario.")
Z <- elicitPt(Z, design.pt = 2,
lower.CI.bound = -2,
median = 1,
upper.CI.bound = 2,
comment = "The second completed elicitation scenario.")
prior <- muSigma(Z, X, fit.method = "KL")
prior$mu
prior$Sigma
``` |

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