coincident_profile {Coinprofile}

Coincident Profile

Description

Returns the coincident profile developed by Martinez et al. (2016). The ideal result is finding the maximum p-value for the lag = 0; otherwise maximum p-value for negative lags suggest leading from x to y, or maximum p-value for positive lags suggest leading from y to x.

Usage

coincident_profile(x, y, frequ = 12, MLag = 6, nvar1 = "name.x",
  nvar2 = "name.y", print.graf = FALSE, iyear = 1,
  lyear = numeric(), imonth = 12, lmonth = numeric(),
  tit1 = "Title.x", tit2 = "Title.y", tit3 = "Title.x.y")

Arguments

x

Univariate time series

y

Univariate time series

frequ

Frequency of x and y. x and y must have the same frequency

MLag

Maximum lag for the coincident profile

nvar1

Name of x

nvar2

Name of y

print.graf

If TRUE returns a panel 2x2 where the superior panel has both plots of x and y with their turning points (maximums black dots lines and minimums red dots lines). The inferior left panel has the matplot of x and y standardized, respectively (x-mean(x))/sd(x). The inferior right panel has the coincident profile where TP shows the number of turning points used.

iyear

The year of the first observation. A single number

lyear

The year of the last observation. A single number

imonth

The amount of months for the first year. A single number

lmonth

The amount of months for the last year. A single number

tit1

Title for the plot x

tit2

Title for the plot y

tit3

Title for the plot x and y

Details

The main output contains two objects: the coincident profile (Profile) and both the lag which has the highest probability and the number of turning points considered to the calculus of the coincident profile (MainLag).

Value

The coincident profile

Author(s)

Wilmer O Martinez R

References

Martinez, W and Nieto, Fabio H and Poncela, P (2016) "Choosing a dynamic common factor as a coincident index", Statistics and Probability Letters, (109), 89-98. http://dx.doi.org/10.1016/j.spl.2015.11.008.

Banerji, A., (1999) "The lead profile and others non-parametrics tools to evaluate survey series as leading indicators", Survey Data for Industry, Research and Economic Policy, selected papers presented at the 24th CIRET Conference, Willington, New Zealand.

Examples

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)

# 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)