# points.unireg: Points method for 'unireg' objects. In uniReg: Unimodal Penalized Spline Regression using B-Splines

## Description

Plotting a unimodal regression object into an existing plot.

## Usage

 ```1 2``` ```## S3 method for class 'unireg' points(x, type="l", ...) ```

## Arguments

 `x` Object of class `"unireg"`, a result of `unireg`. `type` Per default plotting type `"l"` is used for the fitted spline. `...` other parameters to be passed through to the generic `points` functions.

## Details

This is a points method for unimodal regression objects. The spline function is plotted using a grid of x-values equally spaced across the interval on which the spline is defined. The distance between the grid values is given by the minimal distance of the observed x-values (used for fitting) divided by 10.

## Author(s)

Claudia Koellmann

`unireg`,`predict.unireg`,`plot.unireg`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```x <- sort(rep(0:5,20)) n <- length(x) set.seed(41333) func <- function(mu){rnorm(1,mu,0.05)} y <- sapply(dchisq(x,3),func) # plot of data plot(jitter(x), y, xlab="x (jittered)") # fit with default settings fit <- unireg(x, y, g=5) # short overview of the fitted spline fit # plot of true and fitted functions plot(jitter(x), y, xlab="x (jittered)") curve(dchisq(x,3), 0, 5, type="l", col="grey", lwd=2, add=TRUE) points(fit, lwd=2, col="orange") legend("bottomright", legend = c("true mean function", "difference penalized unimodal fit"), col=c("grey","orange"),lwd=c(2,2)) ```

### Example output  ```Fitted unimodal spline of degree 3 with difference penalty of order 2

Coefficients          -0.21 0.03 0.23 0.23 0.18 0.13 0.09 0.07 0.05
Mode of coefficients  3 4
Tuning parameter      20.09
Variance estimate     0
```

uniReg documentation built on May 2, 2019, 6:50 a.m.