Create an interpolation spline, either from `x`

and `y`

vectors (`default`

method), or from a `formula`

/ `data.frame`

combination (`formula`

method).

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

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.

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`

.

# 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 ) # }