get_features: Extract features from multivariate functional data

In pridiltal/outfit: Outlier Detection in Multivariate Functional Data

Description

This function extract features from multivariate functional data.

Usage

get_features(
  data,
  family = "NO",
  df_mu = 5,
  degree_mu = 1,
  df_sig = 4,
  degree_sig = 1
)

Arguments

data	A multivariate funtional dataset with two columns: id and y
family	A gamlss.family object, which is used to define the distribution and the link functions of the various parameters. The distribution families supported by gamlss() can be found in gamlss.family. Default is NO.
df_mu	Degrees of freedom - mu; one can specify df rather than knots; bs() then chooses df-degree knots at suitable quantiles of x (which will ignore missing values).
degree_mu	Degree of the piecewise polynomial-mu; default is 1
df_sig	Degrees of freedom - sigma;
degree_sig	Degree of the piecewise polynomial-sigma; default is 1

Value

An object of class features.

pridiltal/outfit documentation built on Aug. 13, 2020, 12:32 a.m.