MIC.splines.basis: Splines basis functions

In SPREDA: Statistical Package for Reliability Data Analysis

Splines basis functions

Description

Creation splines basis for M_splines, I_splines and C_splines

Usage

MIC.splines.basis(x, df = NULL, knots = NULL, boundary.knots = NULL, 
type = "Ms", degree = 3, delta = 0.01, eq.alloc = F)

Arguments

x	values of covariate
df	number of splines needed which is equal to knots+degree
knots	number of knots needed which does not include the number of knots at the beginning
boundary.knots	the values of boundary knots, which are usually the minimum and maximum of covariate
type	types of splines basis needed, which can be Ms Is or Cs
degree	degree of the splines function
delta	the length of the spans to split the range of covariate
eq.alloc	indicators of whether the knots are equally allocated

Value

list(mat=mat,x=x, df=df, knots=knots,boundary.knots=boundary.knots, type=type,degree=degree,delta=delta)

mat	it is a matrix of splines basis
x	the input of covariate
df	the input of number of splines needed
knots	the input of number of knots needed not including the boundary
boundary.knots	the values of boundary knots
type	type of splines function which can be MS IS or Cs
degree	degree of the splines functions
delta	the length of the spans to split the range of covariate

Author(s)

Yili Hong

References

Hong. Y., Y. Duan, W. Q. Meeker, D. L. Stanley, and X. Gu (2014), Statistical Methods for Degradation Data with Dynamic Covariates Information and an Application to Outdoor Weathering Data, Technometrics, DOI: 10.1080/00401706.2014.915891.

See Also

i.spline.x, m.spline.x

Examples

MIC.splines.basis(x=runif(20), df = NULL, knots = 3, boundary.knots = NULL, 
    type = "Ms", degree = 4, delta = 0.01, eq.alloc = FALSE) 

SPREDA documentation built on April 13, 2025, 5:11 p.m.