plotTwoSampleGP: Plotting fitted GP models for two-sample model

In PROBIC/GPrank: Gaussian Process Ranking of Multiple Time Series

Description

Function for plotting fitted GP models within its confidence region of 2 standard deviations for the two-sample model.

Usage

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

Arguments

model	GP model to be plotted.
index	sample index of the model to be plotted from the two-sample model.
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]; Antti Honkela, [e-mail]

Examples

x=list(as.matrix(seq(1,10)), as.matrix(seq(1,10)))
y=list(as.matrix(sin(x[[1]])), as.matrix(cos(x[[2]])))
v=list(as.matrix(runif(10,0,0.2)), as.matrix(runif(10,0,0.2)))
kernelTypes=c("rbf","white","fixedvariance")
model=constructTwoSampleModel(x,y,v,kernelTypes)
col_item=getColorVector()[1]
index=1
ylimits=c(min(y[[index]])-0.1,max(y[[index]])+0.1)

plotTwoSampleGP(model,index,col_item,ylimits)

PROBIC/GPrank documentation built on May 7, 2019, 11:53 p.m.