Make matrix of periodicity (e.g. seasonal) dummies

Auxiliary function that generates periodicity dummies (e.g. seasonal dummies) for regular time series. The function is similar to, but more general than, the seasonaldummy function in the forecast package.

Usage

periodicdummies(x, values=1)

Arguments

x

a regular time series (vector or matrix)

values

numeric of length 1 (default) or numeric vector of length equal to frequency(x)

Value

A matrix of class zoo with the periodicity dummies

Author

Genaro Sucarrat, http://www.sucarrat.net/

See also

is.regular, zooreg, zoo, ts

Examples

##quarterly dummies:
x <- zooreg(rnorm(30), start=2000, frequency=4)
periodicdummies(x)
#>         dum1 dum2 dum3 dum4
#> 2000 Q1    1    0    0    0
#> 2000 Q2    0    1    0    0
#> 2000 Q3    0    0    1    0
#> 2000 Q4    0    0    0    1
#> 2001 Q1    1    0    0    0
#> 2001 Q2    0    1    0    0
#> 2001 Q3    0    0    1    0
#> 2001 Q4    0    0    0    1
#> 2002 Q1    1    0    0    0
#> 2002 Q2    0    1    0    0
#> 2002 Q3    0    0    1    0
#> 2002 Q4    0    0    0    1
#> 2003 Q1    1    0    0    0
#> 2003 Q2    0    1    0    0
#> 2003 Q3    0    0    1    0
#> 2003 Q4    0    0    0    1
#> 2004 Q1    1    0    0    0
#> 2004 Q2    0    1    0    0
#> 2004 Q3    0    0    1    0
#> 2004 Q4    0    0    0    1
#> 2005 Q1    1    0    0    0
#> 2005 Q2    0    1    0    0
#> 2005 Q3    0    0    1    0
#> 2005 Q4    0    0    0    1
#> 2006 Q1    1    0    0    0
#> 2006 Q2    0    1    0    0
#> 2006 Q3    0    0    1    0
#> 2006 Q4    0    0    0    1
#> 2007 Q1    1    0    0    0
#> 2007 Q2    0    1    0    0

##monthly dummies:
y <- zooreg(rnorm(30), start=c(2000,1), frequency=12)
periodicdummies(y)
#>          dum1 dum2 dum3 dum4 dum5 dum6 dum7 dum8 dum9 dum10 dum11 dum12
#> Jan 2000    1    0    0    0    0    0    0    0    0     0     0     0
#> Feb 2000    0    1    0    0    0    0    0    0    0     0     0     0
#> Mar 2000    0    0    1    0    0    0    0    0    0     0     0     0
#> Apr 2000    0    0    0    1    0    0    0    0    0     0     0     0
#> May 2000    0    0    0    0    1    0    0    0    0     0     0     0
#> Jun 2000    0    0    0    0    0    1    0    0    0     0     0     0
#> Jul 2000    0    0    0    0    0    0    1    0    0     0     0     0
#> Aug 2000    0    0    0    0    0    0    0    1    0     0     0     0
#> Sep 2000    0    0    0    0    0    0    0    0    1     0     0     0
#> Oct 2000    0    0    0    0    0    0    0    0    0     1     0     0
#> Nov 2000    0    0    0    0    0    0    0    0    0     0     1     0
#> Dec 2000    0    0    0    0    0    0    0    0    0     0     0     1
#> Jan 2001    1    0    0    0    0    0    0    0    0     0     0     0
#> Feb 2001    0    1    0    0    0    0    0    0    0     0     0     0
#> Mar 2001    0    0    1    0    0    0    0    0    0     0     0     0
#> Apr 2001    0    0    0    1    0    0    0    0    0     0     0     0
#> May 2001    0    0    0    0    1    0    0    0    0     0     0     0
#> Jun 2001    0    0    0    0    0    1    0    0    0     0     0     0
#> Jul 2001    0    0    0    0    0    0    1    0    0     0     0     0
#> Aug 2001    0    0    0    0    0    0    0    1    0     0     0     0
#> Sep 2001    0    0    0    0    0    0    0    0    1     0     0     0
#> Oct 2001    0    0    0    0    0    0    0    0    0     1     0     0
#> Nov 2001    0    0    0    0    0    0    0    0    0     0     1     0
#> Dec 2001    0    0    0    0    0    0    0    0    0     0     0     1
#> Jan 2002    1    0    0    0    0    0    0    0    0     0     0     0
#> Feb 2002    0    1    0    0    0    0    0    0    0     0     0     0
#> Mar 2002    0    0    1    0    0    0    0    0    0     0     0     0
#> Apr 2002    0    0    0    1    0    0    0    0    0     0     0     0
#> May 2002    0    0    0    0    1    0    0    0    0     0     0     0
#> Jun 2002    0    0    0    0    0    1    0    0    0     0     0     0