gamm4.test (version 0.1.0)

plot.gamtest: Plot a gamtest Object

Description

This function plots the semiparametric estimation of nonlinear curves and surface.

Usage

# S3 method for gamtest
plot(x, test.statistic = FALSE,
  test.stat.type = "density", main = "", n = 256,
  legend.position = "topright", se.est = FALSE, data.pts = FALSE,
  type = "contour", ...)

Arguments

x

A gamtest object.

test.statistic

If TRUE, plot the density of the test statistic under null hypothesis; if FALSE, plot the estimated curves/surfaces.

test.stat.type

must have "test.statistic=TRUE". Default is "test.stat.type=density". If "test.stat.type=hist", plot the histogram of the test statistic under null.

main

The title of the plot.

n

The number of points that are used to draw the curves or surfaces in the plot.

legend.position

the position of legend in the plot: "topright", "topleft", "bottomright", "bottomleft", etc.

se.est

If TRUE, plot the pointwise 95% confidence intervals of curves; if FALSE, don't plot the pointwise confidence intervals.

data.pts

If TRUE, plot raw data points. If FALSE, only plot estimated curves/surfaces.

type

Only used for ploting surfaces. If "type=contour",then contour plot from vis.gam function in mgcv package; if "type=persp", then plot persp from vis.gam function; if "type=plotly.persp", then plot persp from plotly package.

...

Other options from package ``mgcv'' ``vis.gam()'' function.

Details

This function is to plot a gamtest object. If "test.statistic=TRUE", a density plot of the test statistic under null hypothesis will be generated; if "test.statistic=FALSE", the estimated curves/surfaces for all groups are drawn.

See Also

gam gamm4 gamm4.grptest gam.grptest

Examples

# NOT RUN {
n1 <- 200
x1 <- runif(n1,min=0, max=3)
sd1 <- 0.2
e1 <- rnorm(n1,sd=sd1)
y1 <- sin(2*x1) + cos(2*x1) + e1

n2 <- 120
x2 <- runif(n2, min=0, max=3)
sd2 <- 0.25
e2 <- rnorm(n2, sd=sd2)
y2 <- sin(2*x2) + cos(2*x2) + x2 + e2

data.bind <- rbind(cbind(x1,y1,1), cbind(x2,y2,2))
data.bind <- data.frame(data.bind)
colnames(data.bind)=c('x','y','group')

t1 <- gam.grptest(y~s(x,bs="cr"),test=~group,data=data.bind)
t1
plot(t1)
plot(t1,test.statistic=TRUE)

########
## Semiparametric test the equality for regression surfaces
## Simulate data sets

n1 <- 200
x11 <- runif(n1,min=0, max=3)
x12 <- runif(n1,min=0, max=3)
sd1 <- 0.2
e1 <- rnorm(n1,sd=sd1)
y1 <- 2*x11^2 + 3*x12^2  + e1

n2 <- 120
x21 <- runif(n2, min=0, max=3)
x22 <- runif(n2, min=0, max=3)
sd2 <- 0.25
e2 <- rnorm(n2, sd=sd2)
y2 <- 2*x21^2 + 3*x22^2 + 4*sin(2*pi*x21) + e2

n3 <- 150
x31 <- runif(n3,min=0, max=3)
x32 <- runif(n3,min=0, max=3)
sd3 <- 0.2
e3 <- rnorm(n3,sd=sd1)
y3 <- 2*x31^2 + 3*x32^2  + e3

data.bind <- rbind(cbind(x11, x12 ,y1,1), cbind(x21, x22, y2,2), cbind(x31, x32, y3,3))
data.bind <- data.frame(data.bind)
colnames(data.bind)=c('x1','x2', 'y','group')

tspl <- gam.grptest(y~te(x1,x2),test=~group,data=data.bind,N.boot=200,m=225,parallel=FALSE)
tspl$p.value #p-value
plot(tspl)
plot(tspl,test.statistic = TRUE)
plot(tspl,type="plotly.persp")
plot(tspl,type="plotly.persp", data.pts=TRUE)
# }
# NOT RUN {
# }