A class for (univariate) functional data
The funData class represents functional data on d-dimensional
domains. The two slots represent the domain (x-values) and the values of the
different observations (y-values).
## S4 method for signature 'list,array' funData(argvals, X) ## S4 method for signature 'numeric,array' funData(argvals, X) ## S4 method for signature 'funData' show(object) ## S4 method for signature 'funData' names(x) ## S4 replacement method for signature 'funData' names(x) <- value ## S4 method for signature 'funData' str(object, ...) ## S4 method for signature 'funData' summary(object, ...)
argvals |
A list of numeric vectors or a single numeric vector, giving the sampling points in the domains. See Details. |
X |
An array of dimension N x M (for one-dimensional
domains, or N x M_1 x … x
M_d for higher-dimensional domains), giving the observed values for
N individuals. Missing values can be included via |
object |
A |
x |
The |
value |
The names to be given to the |
... |
Other parameters passed to |
Functional data can be seen as realizations of a random process
X: T -> IR
on a d-dimensional
domain T. The data is usually sampled on a fine grid
T subset of T, which is represented in the
argvals slot of a funData object. All observations are assumed
to be sampled over the same grid T, but can contain missing values
(see below). If T is one-dimensional, argvals
can be supplied either as a numeric vector, containing the x-values or as a
list, containing such a vector. If T is
higher-dimensional, argvals must always be supplied as a list,
containing numeric vectors of the x-values in dimensions
1,…,d.
The observed values are represented in the X slot of a funData
object, which is an array of dimension N x M (for
one-dimensional domains, or N x
M_1 x … x M_d for higher-dimensional domains). Here N equals
the number of observations and M denotes the number of sampling
points (for higher dimensional domains M_i denotes the number of
sampling points in dimension i, i = 1,…, d).
Missing values in the observations are allowed and must be marked by
NA. If missing values occur due to irregular observation points, the
data can be stored alternatively as an object of class
irregFunData.
Generic functions for the funData class include a print method,
plotting and basic arithmetics.
Further methods for funData:
dimSupp,
nObs: Informations about the support dimensions and the number
of observations,
getArgvals, extractObs:
Getting/Setting slot values (instead of accessing them directly via
funData@argvals, funData@X) and extracting single observations or
data on a subset of the domain,
integrate,
norm: Integrate all observations over their domain or
calculating the L^2 norm.
A funData object can be coerced to a multiFunData object using
as.multiFunData(funDataObject).
funData: Constructor for functional data objects with argvals given as list.
funData: Constructor for functional data objects with argvals
given as vector of numerics (only valid for one-dimensional domains).
show: Print basic information about the funData object
in the console. The default console output for funData objects.
names: Get the names of the funData object.
names<-: Set the names of the funData object.
str: A str method for funData objects, giving a compact overview of the structure.
summary: A summary method for funData objects.
argvalsThe domain T of the data. See Details.
XThe functional data samples. See Details.
### Creating a one-dimensional funData object with 2 observations
# Basic
f1 <- new("funData", argvals = list(1:5), X = rbind(1:5,6:10))
# Using the constructor with first argument supplied as array
f2 <- funData(argvals = list(1:5), X = rbind(1:5, 6:10))
# Using the constructor with first argument supplied as numeric vector
f3 <- funData(argvals = 1:5, X = rbind(1:5, 6:10))
# Test if all the same
all.equal(f1,f2)
all.equal(f1,f3)
# Display funData object in the console
f3
# A more realistic object
argvals <- seq(0,2*pi,0.01)
object <- funData(argvals, outer(seq(0.75, 1.25, by = 0.05), sin(argvals)))
# Display / summary give basic information
object
summary(object)
# Use the plot function to get an impression of the data
plot(object)
### Higher-dimensional funData objects with 2 observations
# Basic
g1 <- new("funData", argvals = list(1:5, 1:3),
X = array(1:30, dim = c(2,5,3)))
# Using the constructor
g2 <- funData(argvals = list(1:5, 1:3),
X = array(1:30, dim = c(2,5,3)))
# Test if the same
all.equal(g1,g2)
# Display funData object in the console
g2
# Summarize information
summary(g2)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.