Get the initial estimates for a logistic spline fit by assuming the binomial detection probability

Get the initial estimates for a logistic spline fit by assuming the binomial detection probability

Usage

logitSplines_start(dp, mu, wt, df = 1)

Arguments

dp

A vector of detection proportion in all precursors.

mu

A vector of average observed intensities in all precursors.

wt

A vector of the numbers of trials (samples size).

df

Degrees of freedom for the natural cubic spline.

Value

A list of fitted coefficients and the basis matrix for a spline with some degrees of freedom.

Examples

# See the vignettes.