MIC.splines.basis: Splines basis functions
In SPREDA: Statistical Package for Reliability Data Analysis

Description Usage Arguments Value Author(s) References See Also Examples

Creation splines basis for M_splines, I_splines and C_splines

1 2	MIC.splines.basis(x, df = NULL, knots = NULL, boundary.knots = NULL, type = "Ms", degree = 3, delta = 0.01, eq.alloc = F)

`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

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

Yili Hong

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.

i.spline.x, m.spline.x

1 2	MIC.splines.basis(x=runif(20), df = NULL, knots = 3, boundary.knots = NULL, type = "Ms", degree = 4, delta = 0.01, eq.alloc = FALSE)

Loading required package: survival
Loading required package: nlme
$mat
           [,1]      [,2]       [,3]         [,4] [,5]
 [1,] 1.0228286 0.8578623 0.33885646 0.0496642331    0
 [2,] 0.5858675 0.8283815 1.05214867 0.8230083830    0
 [3,] 0.9187883 0.9514458 0.52738034 0.1145050414    0
 [4,] 0.4793617 0.6846780 0.97793340 1.3960970501    0
 [5,] 0.6523582 0.8995873 0.99934449 0.5828767339    0
 [6,] 0.8959170 0.9632678 0.57154693 0.1347866020    0
 [7,] 0.4934618 0.7047936 1.00362799 1.3032668766    0
 [8,] 1.1482064 0.6592169 0.15599415 0.0130686331    0
 [9,] 1.1733718 0.6082439 0.12682523 0.0092900461    0
[10,] 1.3228894 0.2311999 0.01425827 0.0002974498    0
[11,] 1.0309817 0.8477792 0.32527333 0.0461418787    0
[12,] 0.6522606 0.8994971 0.99945819 0.5831790090    0
[13,] 1.1621786 0.6313682 0.13945922 0.0108583597    0
[14,] 1.3965848 0.0000000 0.00000000 0.0000000000    0
[15,] 1.0175843 0.8641377 0.34770127 0.0520325322    0
[16,] 0.6973195 0.9360947 0.93860908 0.4571702984    0
[17,] 0.7883820 0.9768953 0.78064012 0.2706680183    0
[18,] 0.6752599 0.9194535 0.97037367 0.5156101475    0
[19,] 0.7404332 0.9611669 0.86807234 0.3588616252    0
[20,] 0.6684744 0.9138368 0.97941750 0.5348109141    0

$x
 [1] 0.4183074 0.8559412 0.5089904 0.9946445 0.7777191 0.5298339 0.9751723
 [8] 0.3168586 0.2973978 0.1871618 0.4114659 0.7778300 0.3060190 0.1358703
[15] 0.4227273 0.7277950 0.6329043 0.7520125 0.6818999 0.7595677

$df
NULL

$knots
[1] 3

$boundary.knots
[1] 0.1358703 0.9947445

$type
[1] "Ms"

$degree
[1] 4

$delta
[1] 0.01

attr(,"class")
[1] "MICsplines"