splint {fields} R Documentation

## Cubic spline interpolation

### Description

A fast, FORTRAN based function for cubic spline interpolation.

### Usage

```splint(x, y, xgrid, wt=NULL, derivative=0,lam=0, df=NA, lambda=NULL)
```

### Arguments

 `x` The x values that define the curve or a two column matrix of x and y values. `y` The y values that are paired with the x's. `xgrid` The grid to evaluate the fitted cubic interpolating curve. `derivative` Indicates whether the function or a a first or second derivative should be evaluated. `wt` Weights for different obsrevations in the scale of reciprocal variance. `lam` Value for smoothing parameter. Default value is zero giving interpolation. `lambda` Same as `lam` just to make this easier to remember. `df` Effective degrees of freedom. Default is to use lambda =0 or a df equal to the number of observations.

### Details

Fits a piecewise interpolating or smoothing cubic polynomial to the x and y values. This code is designed to be fast but does not many options in `sreg` or other more statistical implementations. To make the solution well posed the the second and third derivatives are set to zero at the limits of the x values. Extrapolation outside the range of the x values will be a linear function.

It is assumed that there are no repeated x values; use sreg followed by predict if you do have replicated data.

### Value

A vector consisting of the spline evaluated at the grid values in `xgrid`.

### References

See Additive Models by Hastie and Tibshriani.

sreg, Tps

### Examples

```x<- seq( 0, 120,,200)

# an interpolation
splint(rat.diet\$t, rat.diet\$trt,x )-> y

plot( rat.diet\$t, rat.diet\$trt)
lines( x,y)
#( this is weird and not appropriate!)

# the following two smooths should be the same

splint( rat.diet\$t, rat.diet\$con,x, df= 7)-> y1

# sreg function has more flexibility than splint but will
# be slower for larger data sets.

sreg( rat.diet\$t, rat.diet\$con, df= 7)-> obj
predict(obj, x)-> y2

# in fact predict.sreg interpolates the predicted values using splint!

# the two predicted lines (should) coincide
lines( x,y1, col="red",lwd=2)
lines(x,y2, col="blue", lty=2,lwd=2)

```

[Package fields version 8.4-1 Index]