plotGP: Plotting fitted GP models

In GPrank: Gaussian Process Ranking of Multiple Time Series

Description

Function for plotting fitted GP model within its confidence region of 2 standard deviations.

Usage

plotGP(model, col_item = "gray", ylimits = NULL, write_xticks = TRUE,
  write_yticks = TRUE, jitterx = FALSE)

Arguments

model	GP model to be plotted.
col_item	RGB color code which will be used for the color of the GP plot.
ylimits	Numeric vector which contains minimum and maximum limits for the y axis.
write_xticks	Boolean: whether to write x ticks and labels or not
write_yticks	Boolean: whether to write y ticks and labels or not
jitterx	Boolean: whether to jitter duplicated x values or not

Value

Creates the plot of the fitted GP model.

Author(s)

Hande Topa, [e-mail]

Examples

x=as.matrix(seq(1,10))
y=as.matrix(sin(x))
v=as.matrix(runif(10,0,0.5))
kernelTypes=c("rbf","white","fixedvariance")
model=constructModel(x,y,v,kernelTypes)
col_item=getColorVector()[1]
ylimits=c(min(y)-0.1,max(y)+0.1)
plotGP(model,col_item,ylimits)

GPrank documentation built on May 2, 2019, 3:35 p.m.