NLL: Non Log-Linear effect

In flexrsurv: Flexible Relative Survival Analysis

Non Log-Linear effect

Description

Generate the spline basis matrix for non log-linear effect.

Usage

NLL(x, 
    Spline = c("b-spline", "tp-spline", "tpi-spline"), 
    Knots = NULL, 
    Degree = 3, 
    Intercept = FALSE,
    Boundary.knots = range(x), 
    Keep.duplicates = TRUE, 
    outer.ok = TRUE, 
    ...)

Arguments

x	the predictor variable.
Spline	a character string specifying the type of spline basis. "b-spline" for B-spline basis, "tp-spline" for truncated power basis and "tpi-spline" for monotone (increasing) truncated power basis.
Knots	the internal breakpoints that define the spline used to estimate the NLL effect. By default there are none.
Degree	degree of splines which are considered.
Intercept	a logical value indicating whether intercept/first basis of spline should be considered.
Boundary.knots	range of variable which is analysed.
Keep.duplicates	Should duplicate interior knots be kept or removed. Defaults is FALSE, which removes duplicate knots with a warning if duplicate interior knots are found.
outer.ok	logical indicating how are managed x values outside the knots. If FALSE, return NA, if TRUE, return 0 for the corresponding x values.
...	not used

Details

NLL is based on package orthogonalsplinebasis

See Also

NPH and NPHNLL.

flexrsurv documentation built on June 7, 2023, 5:09 p.m.