series_split {RecordTest} | R Documentation |
Split Series
Description
The vector X
of length T
is broken into
Mcols
blocks, each part containing T/\code{Mcols}
elements.
If the vector X
represents consecutive daily values in a year, then
Mcols = 365
is preferred. This function rearranges X
into a
matrix format, where each column is the vector of values at the same day
of the year. For monthly data in a year, Mcols = 12
should be used.
Usage
series_split(X, Mcols = 365)
Arguments
X |
A numeric vector. |
Mcols |
An integer number, giving the number of columns in the final matrix. |
Details
This function is used in the data preparation (or pre-processing) often required to apply the exploratory and inference tools based on theory of records within this package when the time series presents seasonality.
This function transforms a vector into a matrix, applying the
following procedure: the first row of the matrix is built of the first
Mcols
elements of the vector, the second row by the Mcols
following elements, and so on.
The length of the vector must be a multiple of Mcols
(see Note otherwise).
In the case of a vector of daily values, Mcols
is usually 365,
so that the first column corresponds to all the values observed at the
1st of January, the second to the 2nd of January, etc.
If X_{t,m}
represents the value in day m
of year t
, then if
\code{X} = (X_{1,1},X_{1,2},\ldots,X_{1,365},X_{2,1},X_{2,2},\ldots,X_{T,365}),
applying series_split
to X
returns the following matrix:
\left( \begin{array}{cccc}
X_{1,1} & X_{1,2} & \cdots & X_{1,365} \\
X_{2,1} & X_{2,2} & \cdots & X_{2,365} \\
\vdots & \vdots & & \vdots \\
X_{T,1} & X_{T,2} & \cdots & X_{T,365}
\end{array} \right)_{T \times 365}.
Value
A matrix with Mcols
columns.
Note
series_double
can be implemented for the same purpose as
this function but without requiring that the length of X
be
divisible by Mcols
. It removes the first elements of X
until
its length is divisible by Mcols
.
Author(s)
Jorge Castillo-Mateo
References
Cebrián AC, Castillo-Mateo J, Asín J (2022). “Record Tests to Detect Non Stationarity in the Tails with an Application to Climate Change.” Stochastic Environmental Research and Risk Assessment, 36(2), 313-330. doi:10.1007/s00477-021-02122-w.
See Also
series_double
, series_record
,
series_rev
, series_ties
,
series_uncor
, series_untie
Examples
series_split(1:100, Mcols = 10)
TxZ <- series_split(TX_Zaragoza$TX)
dim(TxZ)