Compute starting values for optimization — compute

Obtains rough starting values for the beta regression parameters by fitting a quasi-binomial GLM on the midpoint response. This provides a reasonable initialization for the interval likelihood optimizer.

Usage

compute_start(
  formula,
  data,
  link = NULL,
  link_phi = NULL,
  ncuts = 100L,
  lim = 0.5,
  repar = 2L,
  interval = "mid"
)

Arguments

formula: A Formula object (possibly multi-part).
data: Data frame.
link: Mean link function name (NULL: default for repar).
link_phi: Dispersion link function name (NULL: default for repar).
ncuts: Maximum score \(K\) (scale \(0, \ldots, K\)).
lim: Uncertainty half-width.
repar: Reparameterization scheme. Under repar = 0 the shapes are started by the method of moments on the midpoint response (\(f = m(1-m)/v - 1\), \(p = m f\), \(q = (1-m) f\)).
interval: Interval direction used when data is not prepared.

Value

Named numeric vector of starting values.