LPDistance | R Documentation |
Computes the distance based on the chosen Lp norm between a pair of numeric vectors.
LPDistance(x, y, method="euclidean", ...)
x |
Numeric vector containing the first time series. |
y |
Numeric vector containing the second time series. |
method |
A value in "euclidean", "manhattan", "infnorm", "minkowski". |
... |
If method="minkowski" a positive integer value must be specified for |
The distances based on Lp norms are computed between two numeric vectors using the following formulas:
Euclidean distance: √{(x_i-y_i)^2)}
Manhattan distance: ∑{|x_i-y_i|}
Infinite norm distance: \max{|x_i-y_i|}
Minkowski distance: √[p]{(x_i-y_i)^p)}
The two series must have the same length. Furthermore, in the case of the Minkowski distance, p
must be specified as a positive integer value.
d |
The computed distance between the pair of series. |
Usue Mori, Alexander Mendiburu, Jose A. Lozano.
These distances are also implemeted in separate functions. For more information see EuclideanDistance
, ManhattanDistance
, MinkowskiDistance
and InfNormDistance
To calculate this distance measure using ts
, zoo
or xts
objects see TSDistances
. To calculate distance matrices of time series databases using this measure see TSDatabaseDistances
.
# The objects example.series1 and example.series2 are two # numeric series of length 100 contained in the TSdist package. data(example.series1) data(example.series2) # For information on their generation and shape see help # page of example.series. help(example.series) # Compute the different Lp distances # Euclidean distance LPDistance(example.series1, example.series2, method="euclidean") # Manhattan distance LPDistance(example.series1, example.series2, method="manhattan") # Infinite norm distance LPDistance(example.series1, example.series2, method="infnorm") # Minkowski distance with p=3. LPDistance(example.series1, example.series2, method="minkowski", p=3)
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