getSmoothBounds: Get smooth parametric boundaries for efficacy and futility
In aaronjfisher/designOptim: Design optimizer

Description Usage Arguments Value References Examples

A general parametric form for allocating alpha or creating futility boundaries. For details, see Fisher and Rosenblum (2016).

1 2	getSmoothBounds(n_per_stage, delta_vec, coefficients_vec, intercepts_vec, takeDiffs)

`n_per_stage`	vector of sample sizes, or a vector proportional to these sample sizes
`delta_vec`	a vector with elements greater than or equal to 0, one for each boundary to be computed (e.g. one for H01, one for H02, and one for H0C).
`coefficients_vec`	a vector of constants, one for each boundary to be computed (e.g. one for H01, one for H02, and one for H0C)
`intercepts_vec`	a vector of constants to be added to the set to zero for efficacy boundaries
`takeDiffs`	set to TRUE if calculating efficacy boundaries

A matrix with each row corresponding to one boundary (one hypothesis).

Aaron Fisher and Michael Rosenblum (2016). Stochastic Optimization of Adaptive Enrichment Designs for Two Subpopulations. http://biostats.bepress.com/jhubiostat/paper279/

getSmoothBounds(
	  n_per_stage=1:5,
	  intercepts_vec=c(0,0,1,1,0,1),
	  delta_vec=c(1,1,1,1,1,1),
	  coefficients_vec=c(1,1,1,1,2,2),
  takeDiffs=FALSE
	  )