plot.fpcat {dad}

Plotting scores of principal component analysis of density functions among time

Description

Applies to an object of class "fpcat" (see details of the fpcat function). Plots the scores.

Usage

## S3 method for class 'fpcat'
plot(x, nscore=c(1, 2), main = "PCA of probability density functions",
    sub.title = NULL, ...)

Arguments

x

object of class "fpcat" (returned by fpcat).

nscore

numeric or length 2 numeric vector. If it is a length 2 numeric vector (default), it contains the numbers of the score vectors to be plotted. If it is a single value, it is the number of the score which is plotted among time.

Warning: The components of nscore cannot be greater than the nb.factors argument in the call of the fpcat function.

main

this argument to title has an useful default here.

sub.title

string. Subtitle to be added to each graph.

...

optional arguments to plot methods.

Details

Plots:

• if nscore is a length 2 vector (default): the principal scores returned by the fpcat function with arrows from the point corresponding to each time to the next one.

• if nscore is a single value, the principal scores among time with arrows from each time to the next one.

Author(s)

Rachid Boumaza, Pierre Santagostini, Smail Yousfi, Gilles Hunault, Sabine Demotes-Mainard

References

Boumaza, R., Yousfi, S., Demotes-Mainard, S. (2015). Interpreting the principal component analysis of multivariate density functions. Communications in Statistics - Theory and Methods, 44 (16), 3321-3339.

See Also

fpcat; print.fpcat

Examples

times <- as.Date(c("2017-03-01", "2017-04-01", "2017-05-01", "2017-06-01"))
x1 <- data.frame(z1=rnorm(6,1,5), z2=rnorm(6,3,3))
x2 <- data.frame(z1=rnorm(6,4,6), z2=rnorm(6,5,2))
x3 <- data.frame(z1=rnorm(6,7,2), z2=rnorm(6,8,4))
x4 <- data.frame(z1=rnorm(6,9,3), z2=rnorm(6,10,2))
ft <- foldert(x1, x2, x3, x4, times = times, rows.select="intersect")
print(ft)
result <- fpcat(ft)
plot(result)
plot(result,  nscore = c(1, 2))
plot(result,  nscore = 1)
plot(result)