total_mixed_c_correlation_2 {otsfeatures} | R Documentation |
Computes the total mixed cumulative quantile correlation (TMCQC) between an ordinal and a real-valued time series
Description
total_mixed_c_correlation_2
returns the TMCQC
between an ordinal and a real-valued time series
Usage
total_mixed_c_correlation_2(
o_series,
n_series,
lag = 1,
states,
features = FALSE
)
Arguments
o_series |
An OTS. |
n_series |
A real-valued time series. |
lag |
The considered lag (default is 1). |
states |
A numerical vector containing the corresponding states. |
features |
Logical. If |
Details
Given a OTS of length with range
,
, and
the cumulative binarized time series, which is defined as
,
with
such that
if
(
), the function computes the estimated TMCQC given by
where
, with
being a
-length real-valued time series,
a probability
level,
the indicator function and
the quantile
function of the corresponding real-valued process. If
features = TRUE
, the function
returns a vector whose components are the quantities ,
.
Value
If features = FALSE
(default), returns the value of the TMCQC. Otherwise, the function
returns a vector of features, i.e., the vector contains the features employed to compute the
TMCLC.
Author(s)
Ángel López-Oriona, José A. Vilar
Examples
tmclc <- total_mixed_c_correlation_2(o_series = SyntheticData1$data[[1]],
n_series = rnorm(600), states = 0 : 5) # Computing the TMCQC
# between the first series in dataset SyntheticData1 and white noise
feature_vector <- total_mixed_c_correlation_2(o_series = SyntheticData1$data[[1]],
n_series = rnorm(600), states = 0 : 5, features = TRUE) # Computing the corresponding
# vector of features