Description
Coincident Profile.
Description
Builds the coincident profile proposed by Martinez, W and Nieto, Fabio H and Poncela, P (2016) <doi:10.1016/j.spl.2015.11.008>. This methodology studies the relationship between a couple of time series based on the the set of turning points of each time series. The coincident profile establishes if two time series are coincident, or one of them leads the second.
README.md
Coinprofile
This package allows us to calculate the turning points from the Bry and Boschan (1971) methodology. The main goal of Coinprofile is to build the coincident profile according to Martinez et al (2016).
Installation
You can install the released version of Coinprofile from CRAN with:
install.packages("Coinprofile")
Example
This is a basic example which shows you how to solve a common problem:
library(Coinprofile)
## basic example code
set.seed(123)
w <- seq(-3, 7, length.out = 100)
x1 <- sin(pi*w)+rnorm(100,0,0.1)
x2 <- sin(pi*w-0.1)+rnorm(100,0,0.1)
coincident_profile(x1, x2, 4, 5, "name.x", "name.y", TRUE, 1991, 2015, 4, 4)
#> $Profile
#> p.value lags
#> p(-5) 0.78125 -5
#> p(-4) 0.78125 -4
#> p(-3) 0.78125 -3
#> p(-2) 0.78125 -2
#> p(-1) 1.56250 -1
#> p(0) 75.00000 0
#> p(1) 10.93750 1
#> p(2) 1.56250 2
#> p(3) 0.78125 3
#> p(4) 0.78125 4
#> p(5) 0.78125 5
#>
#> $MainLag
#> lag_MaxP-value name.x name.y Amount_TP_used
#> 1 0 name.x name.y 8
# In this example x leads y three periods
set.seed(123)
w <- seq(-3, 7, length.out = 100)
x <- sin(pi*w)+rnorm(100,0,0.1)
y <- sin(pi*w-1)+rnorm(100,0,0.1)
coincident_profile(x, y, 4, 6, "name.x", "name.y", TRUE, 1991, 2015, 4, 4)
#> $Profile
#> p.value lags
#> p(-6) 0.78125 -6
#> p(-5) 0.78125 -5
#> p(-4) 1.56250 -4
#> p(-3) 100.00000 -3
#> p(-2) 0.78125 -2
#> p(-1) 0.78125 -1
#> p(0) 0.78125 0
#> p(1) 0.78125 1
#> p(2) 0.78125 2
#> p(3) 0.78125 3
#> p(4) 0.78125 4
#> p(5) 0.78125 5
#> p(6) 0.78125 6
#>
#> $MainLag
#> lag_MaxP-value name.x name.y Amount_TP_used
#> 1 -3 name.x name.y 8