# interpSpline

##### Create an Interpolation Spline

Create an interpolation spline, either from `x`

and `y`

vectors (`default`

method), or from a `formula`

/ `data.frame`

combination (`formula`

method).

- Keywords
- models

##### Usage

```
interpSpline(obj1, obj2, bSpline = FALSE, period = NULL,
ord = 4L,
na.action = na.fail, sparse = FALSE)
```

##### Arguments

- obj1
either a numeric vector of

`x`

values or a formula.- obj2
if

`obj1`

is numeric this should be a numeric vector of the same length. If`obj1`

is a formula this can be an optional data frame in which to evaluate the names in the formula.- bSpline
if

`TRUE`

the b-spline representation is returned, otherwise the piecewise polynomial representation is returned. Defaults to`FALSE`

.- period
an optional positive numeric value giving a period for a periodic interpolation spline.

- ord
an integer specifying the spline

*order*, the number of coefficients per interval. \(ord = d+1\) where \(d\) is the*degree*polynomial degree. Currently, only cubic splines (`ord = 4`

) are implemented.- na.action
a optional function which indicates what should happen when the data contain

`NA`

s. The default action (`na.omit`

) is to omit any incomplete observations. The alternative action`na.fail`

causes`interpSpline`

to print an error message and terminate if there are any incomplete observations.- sparse
logical passed to the underlying

`splineDesign`

. If true, saves memory and is faster when there are more than a few hundred points.

##### Value

An object that inherits from (S3) class `spline`

. The object can be in
the B-spline representation, in which case it will be of class
`nbSpline`

for natural B-spline, or in the piecewise polynomial
representation, in which case it will be of class `npolySpline`

.

##### See Also

##### Examples

`library(splines)`

```
# NOT RUN {
<!-- % tests also in ../tests/spline-tst.R -->
# }
# NOT RUN {
require(graphics); require(stats)
ispl <- interpSpline( women$height, women$weight )
ispl2 <- interpSpline( weight ~ height, women )
# ispl and ispl2 should be the same
plot( predict( ispl, seq( 55, 75, length.out = 51 ) ), type = "l" )
points( women$height, women$weight )
plot( ispl ) # plots over the range of the knots
points( women$height, women$weight )
splineKnots( ispl )
# }
```

*Documentation reproduced from package splines, version 3.6.0, License: Part of R 3.6.0*