# plot.pspfit: Plotting function for 'psNormal', 'psPoisson', 'psBinomial' In JOPS: Practical Smoothing with P-Splines

 plot.pspfit R Documentation

## Plotting function for `psNormal`, `psPoisson`, `psBinomial`

### Description

Plotting function for P-spline smooth with normal, Poisson, or binomial responses (`class pspfit`), with or without standard error bands.

### Usage

``````## S3 method for class 'pspfit'
plot(x, ..., se = 2, xlab = "", ylab = "", col = "black", pch = 1)
``````

### Arguments

 `x` the P-spline object, usually from psNormal, psPoisson, psBinomial. `...` other parameters. `se` a scalar, e.g. `se = 2` to produce twice se bands, set `se` > 0 (or set `se`=0 to supress). `xlab` label for the x-axis. `ylab` label for the y-axis. `col` color for points. `pch` point character.

### Value

 `Plot` a plot of the mean (inverse link) smoothed normal, Poisson, or binomial responses, with or without se bands.

### Author(s)

Paul Eilers and Brian Marx

### References

Eilers, P.H.C. and Marx, B.D. (2021). Practical Smoothing, The Joys of P-splines. Cambridge University Press.

Eilers, P.H.C., Marx, B.D., and Durban, M. (2015). Twenty years of P-splines, SORT, 39(2): 149-186.

### Examples

``````library(JOPS)
#Extract data
library(MASS)
# Get the data
data(mcycle)
x = mcycle\$times
y = mcycle\$accel
fit1 = psNormal(x, y, nseg = 20, bdeg = 3, pord = 2, lambda = .8)
plot(fit1, se = 2, xlab = "time (ms)", ylab = "accel")

library(JOPS)
library(boot)
# Extract the data
Count = hist(boot::coal\$date, breaks=c(1851:1963), plot = FALSE)\$counts
Year = c(1851:1962)
xl = min(Year)
xr = max(Year)

# Poisson smoothing
nseg = 20
bdeg = 3
fit1=psPoisson(Year, Count, xl, xr, nseg, bdeg, pord = 2,
lambda = 1)
names(fit1)
plot(fit1, xlab = "Year", ylab = "Count", se = 2)

library(JOPS)
#Extract data
library(rpart)
Kyphosis = kyphosis\$Kyphosis
Age  =kyphosis\$Age
y = 1 * (Kyphosis == "present")  # make y 0/1
# Binomial smoothing
fit1 = psBinomial(Age, y, xl = min(Age), xr = max(Age), nseg = 20,
bdeg = 3, pord = 2, lambda = 1)
names(fit1)
plot(fit1, xlab = "Age", ylab = '0/1', se = 2)

``````

JOPS documentation built on Sept. 8, 2023, 5:42 p.m.