Well, without further information, I do not know, but try the following
 
library(urca)
example(ca.jo)
trend <- matrix(1:nrow(sjf), ncol = 1)
colnames(trend) <- "trd"
ca.jo(sjf, type = "trace", ecdet = "const", K = 2, spec = "longrun", dumvar = trend)
 
Best,
Bernhard
 
 


________________________________

	Von: Grzegorz Konat [mailto:grzegorz.konat@ibrkk.pl] 
	Gesendet: Donnerstag, 31. März 2011 14:40
	An: Pfaff, Bernhard Dr.; r-help@r-project.org
	Betreff: Re: [R] VECM with UNRESTRICTED TREND
	
	
	'time' was a trend variable from my.data set. Equivalent to the output of the command 'matrix' you just gave me. 
	
	
	So now I did:
	
	
	library(urca)
	data(my.data)
	names(my.data)
	attach(my.data)
	dat1 <- my.data[, c("dY", "X", "dM")]
	mat1 <- matrix(seq(1:nrow(dat1)), ncol = 1)
	args('ca.jo')
	yxm.vecm <- ca.jo(dat1, type = "trace", ecdet = "const", K = 2, spec = "longrun", dumvar=mat1)

	and the output is:

	Error in r[i1, , drop = FALSE] - r[-nrow(r):-(nrow(r) - lag + 1L), , drop = FALSE] : 
	  non-numeric argument to binary operator
	In addition: Warning message:
	In ca.jo(dat1, type = "trace", ecdet = "const", K = 2, spec = "longrun",  :
	No column names in 'dumvar', using prefix 'exo' instead.

	What do I do wrong?

	Best,
	Greg


	2011/3/31 Pfaff, Bernhard Dr. <Bernhard_Pfaff@fra.invesco.com>
	

		
		 

			Hello Bernhard, 
			
			
			thank You so much one again! Now I (more or less) understand the idea, but still have problem with its practical application.
			
			
			I do (somewhat following example 8.1 in your textbook):
			
			
			library(urca)
			data(my.data)
			names(my.data)
			attach(my.data)
			dat1 <- my.data[, c("dY", "X", "dM")]
			dat2 <- cbind(time)
			 
			What is 'time'? Just employ matrix(seq(1:nrow(dat1)), ncol = 1) for creating the trend variable.
			 
			Best,
			Bernhard
			 
			 
			 args('ca.jo')
			yxm.vecm <- ca.jo(dat1, type = "trace", ecdet = "trend", K = 2, spec = "longrun", dumvar=dat2)

			The above code produces following output:

			Error in r[i1, , drop = FALSE] - r[-nrow(r):-(nrow(r) - lag + 1L), , drop = FALSE] : 
			  non-numeric argument to binary operator

			What does that mean? Should I use cbind command to dat1 as well? And doesn't it transform the series into series of integer numbers?

			Thank you once again (especially for your patience).

			Best,
			Greg



			2011/3/31 Pfaff, Bernhard Dr. <Bernhard_Pfaff@fra.invesco.com>
			

				Hello Greg,
				 
				you include your trend as a (Nx1) matrix and use this for 'dumvar'. The matrix 'dumvar' is just added to the VECM as deterministic regressors and while you are referring to case 5, this is basically what you are after, if I am not mistaken. But we aware that this implies a quadratic trend for the levels.
				 
				Best,
				Bernhard


________________________________

					Von: Grzegorz Konat [mailto:grzegorz.konat@ibrkk.pl] 
					Gesendet: Mittwoch, 30. März 2011 20:50
					An: Pfaff, Bernhard Dr.; r-help@r-project.org
					Betreff: Re: [R] VECM with UNRESTRICTED TREND
					
					
					Hello Bernhard, 

					Thank You very much. Unfortunately I'm still not really sure how should I use dummy vars in this context...
					If I have a system of three variables (x, y, z), lag order = 2 and 1 cointegrating relation, what should I do? I mean, what kind of 'pattern' should be used to create those dummy variables, what should they represent and how many of them do I need?

					Many thanks in advance!

					Best,
					Greg
					
					
					2011/3/30 Pfaff, Bernhard Dr. <Bernhard_Pfaff@fra.invesco.com>
					

					Hello Greg,
					
					you can exploit the argument 'dumvar' for this. See ?ca.jo
					
					Best,
					Bernhard
					
					> -----Ursprüngliche Nachricht-----
					> Von: r-help-bounces@r-project.org
					> [mailto:r-help-bounces@r-project.org] Im Auftrag von Grzegorz Konat
					> Gesendet: Mittwoch, 30. März 2011 16:46
					> An: r-help@r-project.org
					> Betreff: [R] VECM with UNRESTRICTED TREND
					
					>
					> Dear All,
					>
					> My question is:
					>
					> how can I estimate VECM system with "unrestricted trend" (aka
					> "case 5") option as a deterministic term?
					>
					> As far as I know, ca.jo in urca package allows for "restricted trend"
					> only [vecm
					> <- ca.jo(data, type = "trace"/"eigen", ecdet = "trend", K =
					> n, spec = "transitory"/"longrun")].
					> Obviously, I don't have to do this in urca, so if another
					> package gives the possibility, please let me know too!
					>
					> Thanks in advance!
					>
					> Greg
					>
					
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					>
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					> https://stat.ethz.ch/mailman/listinfo/r-help
					> PLEASE do read the posting guide
					> http://www.R-project.org/posting-guide.html
					> and provide commented, minimal, self-contained, reproducible code.
					>
					
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