R help - May 2017 - Error: invalid type (closure) for the variable 'time' - object specific trend

> On 12 May 2017, at 16:40 , Tobias Christoph <s3tochri at
uni-bayreuth.de> wrote:
> 
> Hey guys,
> 
> thanks a lot for your tips. The regression is finally running. As you 
> said, I had to integrate the column "year" in the function
"time" in R.
> 
> So I used the following formula: *plm(log(revenue) ~ log(supply) + 
> factor(town)*time(year), data=R_Test_log_Neu)*
Um, that might not do what I think you think it does. time() gives you the
"vector of times at which a time series was sampled". If you feed it
any regular vector, it just gives the numbers 1:n, witness
> time(rnorm(20))
 [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20
attr(,"tsp")
[1]  1 20  1

I suspect you just want "year" in the formula.
> 
> So I have now sucessfully added a linear trend to my regression model? 
> Another question that concernes me is how to add a quadratic trend 
> instead of a linear trend. Can I just square the column "year"?
In principle, yes, but as others have pointed out, centering the variable may be
a good idea, for numerical stability.

-pd
> 
> Enjoy your weekend,
> 
> Toby
> 
> _My results see below:_
> 
> Balanced Panel: n=11, T=12, N=132
> 
> Residuals :
>     Min.  1st Qu.   Median  3rd Qu.     Max.
> -0.09610 -0.02370 -0.00152  0.01980  0.14000
> 
> Coefficients :
>                             Estimate Std. Error t-value  Pr(>|t|)
> log(supply)               -0.0080702  0.0133675 -0.6037  0.547411
> factor(town)2:time(year)  -0.0063245  0.0053744 -1.1768  0.242100
> factor(town)3:time(year)   0.0295522  0.0056776  5.2050 1.053e-06 ***
> factor(town)4:time(year)   0.0062191  0.0054152  1.1485  0.253549
> factor(town)5:time(year)   0.0159028  0.0054954  2.8939  0.004681 **
> factor(town)6:time(year)   0.0237112  0.0055395  4.2804 4.316e-05 ***
> factor(town)7:time(year)   0.0410007  0.0055734  7.3565 5.576e-11 ***
> factor(town)8:time(year)   0.0239085  0.0053751  4.4480 2.271e-05 ***
> factor(town)9:time(year)   0.0242342  0.0056855  4.2625 4.619e-05 ***
> factor(town)10:time(year)  0.0105890  0.0053302  1.9866  0.049733 *
> factor(town)11:time(year)  0.0095270  0.0056354  1.6906  0.094065 .
> ---
> Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
> 
> Total Sum of Squares:    0.46388
> Residual Sum of Squares: 0.2001
> R-Squared:      0.56863
> Adj. R-Squared: 0.4292
> F-statistic: 11.8637 on 11 and 99 DF, p-value: 7.3065e-14
> 
> 
> 
> Am 11.05.2017 um 23:17 schrieb David L Carlson:
>> What Rui said, but as important, you have four columns in your data
called "town", "year", "revenue", and
"supply". You do not have a column called "time".
>> 
>> -------------------------------------
>> David L Carlson
>> Department of Anthropology
>> Texas A&M University
>> College Station, TX 77840-4352
>> 
>> -----Original Message-----
>> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Rui
Barradas
>> Sent: Thursday, May 11, 2017 3:36 PM
>> To: Tobias Christoph <s3tochri at uni-bayreuth.de>; Duncan
Murdoch <murdoch.duncan at gmail.com>; r-help at r-project.org
>> Subject: Re: [R] Error: invalid type (closure) for the variable
'time' - object specific trend
>> 
>> Hello,
>> 
>> A closure is, like you say, a function.
>> At an R prompt try:
>> 
>>> typeof(time)
>> [1] "closure"
>> 
>> So like Duncan suggested rename 'time', for instance capitalize
it
>> 'Time'. That should do it.
>> 
>> Hope this helps,
>> 
>> Rui Barradas
>> 
>> 
>> 
>> Em 11-05-2017 21:20, Tobias Christoph escreveu:
>>> Hey Duncan,
>>> 
>>> thank you very much for your quick reply.
>>> 
>>> _My data used:_
>>> 
>>> 1st column(town):1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,...........,11
>>> 
>>> 2nd column(year):1,2,3,4,5,6,7,8,9,10,11,12,1,2,3.......,12
>>> 
>>> 3rd column (revenue):
>>> 
>>> 4th colum (supply):
>>> 
>>> I have now renamed my colums and did the regression again. Now
there is
>>> a problem with R-squared, as it is the sum of 1 now with no given
std.
>>> error and t-value. This is probably due to the fact, that I try to
>>> estimate more parameters than data.
>>> 
>>> To add a linear trend I found the following formular:*lm(y ~ x1 +
>>> factor(ccode)*time, data=df)*
>>> 
>>> I try to I decode it for and use it for my regression:
*plm(log(revenue)
>>> ~ log(supply) + factor(town)*time, data=R_Test_log_Neu)*
>>> 
>>> When I do this regression I will get the original error:
"invalid type
>>> (closure) for the variable 'time' - object specific
trend"
>>> 
>>> With the notation"time" not my colum is meant, but
probably the command
>>> "time" in R.
>>> 
>>> Can you follow my thoughts?
>>> 
>>> Tobi
>>> 
>>> 
>>> 
>>> 
>>> 
>>> 
>>> Am 11.05.2017 um 17:23 schrieb Duncan Murdoch:
>>>> Duncan Murdoch
>>> ______________________________________________
>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more,
see
>>> 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.
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> 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.
>> 
> 
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com

Hey Peter,

thank you. Yes, I want to have "year" in the varibale.
But if I use "*town*year*" as a furmula, R will create new factor 
variable with n levels, where n = (num of towns) x (num of years). What 
I'm trying to do is create 50 (town x year) variables such that 
town1xyear is 1,2,3... when town== 1 and zero otherwise, repeat for 
town2xyear, where state == 2, etc.

It is now clear? Sorry for my bad explanations.

Toby


Am 12.05.2017 um 23:23 schrieb peter dalgaard:
>> On 12 May 2017, at 16:40 , Tobias Christoph <s3tochri at
uni-bayreuth.de> wrote:
>>
>> Hey guys,
>>
>> thanks a lot for your tips. The regression is finally running. As you
>> said, I had to integrate the column "year" in the function
"time" in R.
>>
>> So I used the following formula: *plm(log(revenue) ~ log(supply) +
>> factor(town)*time(year), data=R_Test_log_Neu)*
> Um, that might not do what I think you think it does. time() gives you the
"vector of times at which a time series was sampled". If you feed it
any regular vector, it just gives the numbers 1:n, witness
>
>> time(rnorm(20))
>   [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20
> attr(,"tsp")
> [1]  1 20  1
>
> I suspect you just want "year" in the formula.
>
>> So I have now sucessfully added a linear trend to my regression model?
>> Another question that concernes me is how to add a quadratic trend
>> instead of a linear trend. Can I just square the column
"year"?
> In principle, yes, but as others have pointed out, centering the variable
may be a good idea, for numerical stability.
>
> -pd
>
>> Enjoy your weekend,
>>
>> Toby
>>
>> _My results see below:_
>>
>> Balanced Panel: n=11, T=12, N=132
>>
>> Residuals :
>>      Min.  1st Qu.   Median  3rd Qu.     Max.
>> -0.09610 -0.02370 -0.00152  0.01980  0.14000
>>
>> Coefficients :
>>                              Estimate Std. Error t-value  Pr(>|t|)
>> log(supply)               -0.0080702  0.0133675 -0.6037  0.547411
>> factor(town)2:time(year)  -0.0063245  0.0053744 -1.1768  0.242100
>> factor(town)3:time(year)   0.0295522  0.0056776  5.2050 1.053e-06 ***
>> factor(town)4:time(year)   0.0062191  0.0054152  1.1485  0.253549
>> factor(town)5:time(year)   0.0159028  0.0054954  2.8939  0.004681 **
>> factor(town)6:time(year)   0.0237112  0.0055395  4.2804 4.316e-05 ***
>> factor(town)7:time(year)   0.0410007  0.0055734  7.3565 5.576e-11 ***
>> factor(town)8:time(year)   0.0239085  0.0053751  4.4480 2.271e-05 ***
>> factor(town)9:time(year)   0.0242342  0.0056855  4.2625 4.619e-05 ***
>> factor(town)10:time(year)  0.0105890  0.0053302  1.9866  0.049733 *
>> factor(town)11:time(year)  0.0095270  0.0056354  1.6906  0.094065 .
>> ---
>> Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
>>
>> Total Sum of Squares:    0.46388
>> Residual Sum of Squares: 0.2001
>> R-Squared:      0.56863
>> Adj. R-Squared: 0.4292
>> F-statistic: 11.8637 on 11 and 99 DF, p-value: 7.3065e-14
>>
>>
>>
>> Am 11.05.2017 um 23:17 schrieb David L Carlson:
>>> What Rui said, but as important, you have four columns in your data
called "town", "year", "revenue", and
"supply". You do not have a column called "time".
>>>
>>> -------------------------------------
>>> David L Carlson
>>> Department of Anthropology
>>> Texas A&M University
>>> College Station, TX 77840-4352
>>>
>>> -----Original Message-----
>>> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of
Rui Barradas
>>> Sent: Thursday, May 11, 2017 3:36 PM
>>> To: Tobias Christoph <s3tochri at uni-bayreuth.de>; Duncan
Murdoch <murdoch.duncan at gmail.com>; r-help at r-project.org
>>> Subject: Re: [R] Error: invalid type (closure) for the variable
'time' - object specific trend
>>>
>>> Hello,
>>>
>>> A closure is, like you say, a function.
>>> At an R prompt try:
>>>
>>>> typeof(time)
>>> [1] "closure"
>>>
>>> So like Duncan suggested rename 'time', for instance
capitalize it
>>> 'Time'. That should do it.
>>>
>>> Hope this helps,
>>>
>>> Rui Barradas
>>>
>>>
>>>
>>> Em 11-05-2017 21:20, Tobias Christoph escreveu:
>>>> Hey Duncan,
>>>>
>>>> thank you very much for your quick reply.
>>>>
>>>> _My data used:_
>>>>
>>>> 1st column(town):1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,...........,11
>>>>
>>>> 2nd column(year):1,2,3,4,5,6,7,8,9,10,11,12,1,2,3.......,12
>>>>
>>>> 3rd column (revenue):
>>>>
>>>> 4th colum (supply):
>>>>
>>>> I have now renamed my colums and did the regression again. Now
there is
>>>> a problem with R-squared, as it is the sum of 1 now with no
given std.
>>>> error and t-value. This is probably due to the fact, that I try
to
>>>> estimate more parameters than data.
>>>>
>>>> To add a linear trend I found the following formular:*lm(y ~ x1
+
>>>> factor(ccode)*time, data=df)*
>>>>
>>>> I try to I decode it for and use it for my regression:
*plm(log(revenue)
>>>> ~ log(supply) + factor(town)*time, data=R_Test_log_Neu)*
>>>>
>>>> When I do this regression I will get the original error:
"invalid type
>>>> (closure) for the variable 'time' - object specific
trend"
>>>>
>>>> With the notation"time" not my colum is meant, but
probably the command
>>>> "time" in R.
>>>>
>>>> Can you follow my thoughts?
>>>>
>>>> Tobi
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>> Am 11.05.2017 um 17:23 schrieb Duncan Murdoch:
>>>>> Duncan Murdoch
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and
more, see
>>>> 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.
>>> ______________________________________________
>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more,
see
>>> 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.
>>>
>>
>> 	[[alternative HTML version deleted]]
>>
>> ______________________________________________
>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> 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.

	[[alternative HTML version deleted]]

> On May 13, 2017, at 4:07 AM, Tobias Christoph <s3tochri at
uni-bayreuth.de> wrote:
> 
> Hey Peter,
> 
> thank you. Yes, I want to have "year" in the varibale.
> But if I use "*town*year*" as a furmula, R will create new factor
> variable with n levels, where n = (num of towns) x (num of years). What 
> I'm trying to do is create 50 (town x year) variables such that 
> town1xyear is 1,2,3... when town== 1 and zero otherwise, repeat for 
> town2xyear, where state == 2, etc.
> 
> It is now clear? Sorry for my bad explanations.
I had suggested that you must provide str(R_Test_log_Neu). I'm still
suggesting this would be a good idea.

Since you have not done so, we can only guess at the right course to follow from
your reports of problems and errors. Peter pointed out that the `time` function
was in the 'stats' package (not from plm or elsewhere as I imagined).
You are implying that 'year' is currently a factor value with levels
that appears as the character versions of integers.

You may be able to get closer to what is possible by using:

plm( log(revenue) ~ log(supply) + factor(town) + as.numeric(as.character(year)),
     data=R_Test_log_Neu)

This should fix the problem noted by Peter and avoid the potentially incorrect
construction of the desired linear trend.

If you used the interaction operator "*" between 'town' and
the numeric version of 'year' it will give you two sets of coefficients
involving 'town'. The first set will be the mean deviations from the
base factor level. The other set will be the differences in slopes for the time
trends for each of the (factored) towns from the overall time trend/slope. And
for your data you wouldbe constructing a saturated model ... as you observed in
your first message (which remains in the copied thread below).

-- 
David.
> 
> Toby
> 
> 
> Am 12.05.2017 um 23:23 schrieb peter dalgaard:
>>> On 12 May 2017, at 16:40 , Tobias Christoph <s3tochri at
uni-bayreuth.de> wrote:
>>> 
>>> Hey guys,
>>> 
>>> thanks a lot for your tips. The regression is finally running. As
you
>>> said, I had to integrate the column "year" in the
function "time" in R.
>>> 
>>> So I used the following formula: *plm(log(revenue) ~ log(supply) +
>>> factor(town)*time(year), data=R_Test_log_Neu)*
>> Um, that might not do what I think you think it does. time() gives you
the "vector of times at which a time series was sampled". If you feed
it any regular vector, it just gives the numbers 1:n, witness
>> 
>>> time(rnorm(20))
>>  [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20
>> attr(,"tsp")
>> [1]  1 20  1
>> 
>> I suspect you just want "year" in the formula.
>> 
>>> So I have now sucessfully added a linear trend to my regression
model?
>>> Another question that concernes me is how to add a quadratic trend
>>> instead of a linear trend. Can I just square the column
"year"?
>> In principle, yes, but as others have pointed out, centering the
variable may be a good idea, for numerical stability.
>> 
>> -pd
>> 
>>> Enjoy your weekend,
>>> 
>>> Toby
>>> 
>>> _My results see below:_
>>> 
>>> Balanced Panel: n=11, T=12, N=132
>>> 
>>> Residuals :
>>>     Min.  1st Qu.   Median  3rd Qu.     Max.
>>> -0.09610 -0.02370 -0.00152  0.01980  0.14000
>>> 
>>> Coefficients :
>>>                             Estimate Std. Error t-value 
Pr(>|t|)
>>> log(supply)               -0.0080702  0.0133675 -0.6037  0.547411
>>> factor(town)2:time(year)  -0.0063245  0.0053744 -1.1768  0.242100
>>> factor(town)3:time(year)   0.0295522  0.0056776  5.2050 1.053e-06
***
>>> factor(town)4:time(year)   0.0062191  0.0054152  1.1485  0.253549
>>> factor(town)5:time(year)   0.0159028  0.0054954  2.8939  0.004681
**
>>> factor(town)6:time(year)   0.0237112  0.0055395  4.2804 4.316e-05
***
>>> factor(town)7:time(year)   0.0410007  0.0055734  7.3565 5.576e-11
***
>>> factor(town)8:time(year)   0.0239085  0.0053751  4.4480 2.271e-05
***
>>> factor(town)9:time(year)   0.0242342  0.0056855  4.2625 4.619e-05
***
>>> factor(town)10:time(year)  0.0105890  0.0053302  1.9866  0.049733 *
>>> factor(town)11:time(year)  0.0095270  0.0056354  1.6906  0.094065 .
>>> ---
>>> Signif. codes:  0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
>>> 
>>> Total Sum of Squares:    0.46388
>>> Residual Sum of Squares: 0.2001
>>> R-Squared:      0.56863
>>> Adj. R-Squared: 0.4292
>>> F-statistic: 11.8637 on 11 and 99 DF, p-value: 7.3065e-14
>>> 
>>> 
>>> 
>>> Am 11.05.2017 um 23:17 schrieb David L Carlson:
>>>> What Rui said, but as important, you have four columns in your
data called "town", "year", "revenue", and
"supply". You do not have a column called "time".
>>>> 
>>>> -------------------------------------
>>>> David L Carlson
>>>> Department of Anthropology
>>>> Texas A&M University
>>>> College Station, TX 77840-4352
>>>> 
>>>> -----Original Message-----
>>>> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf
Of Rui Barradas
>>>> Sent: Thursday, May 11, 2017 3:36 PM
>>>> To: Tobias Christoph <s3tochri at uni-bayreuth.de>;
Duncan Murdoch <murdoch.duncan at gmail.com>; r-help at r-project.org
>>>> Subject: Re: [R] Error: invalid type (closure) for the variable
'time' - object specific trend
>>>> 
>>>> Hello,
>>>> 
>>>> A closure is, like you say, a function.
>>>> At an R prompt try:
>>>> 
>>>>> typeof(time)
>>>> [1] "closure"
>>>> 
>>>> So like Duncan suggested rename 'time', for instance
capitalize it
>>>> 'Time'. That should do it.
>>>> 
>>>> Hope this helps,
>>>> 
>>>> Rui Barradas
>>>> 
>>>> 
>>>> 
>>>> Em 11-05-2017 21:20, Tobias Christoph escreveu:
>>>>> Hey Duncan,
>>>>> 
>>>>> thank you very much for your quick reply.
>>>>> 
>>>>> _My data used:_
>>>>> 
>>>>> 1st
column(town):1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,...........,11
>>>>> 
>>>>> 2nd column(year):1,2,3,4,5,6,7,8,9,10,11,12,1,2,3.......,12
>>>>> 
>>>>> 3rd column (revenue):
>>>>> 
>>>>> 4th colum (supply):
>>>>> 
>>>>> I have now renamed my colums and did the regression again.
Now there is
>>>>> a problem with R-squared, as it is the sum of 1 now with no
given std.
>>>>> error and t-value. This is probably due to the fact, that I
try to
>>>>> estimate more parameters than data.
>>>>> 
>>>>> To add a linear trend I found the following formular:*lm(y
~ x1 +
>>>>> factor(ccode)*time, data=df)*
>>>>> 
>>>>> I try to I decode it for and use it for my regression:
*plm(log(revenue)
>>>>> ~ log(supply) + factor(town)*time, data=R_Test_log_Neu)*
>>>>> 
>>>>> When I do this regression I will get the original error:
"invalid type
>>>>> (closure) for the variable 'time' - object specific
trend"
>>>>> 
>>>>> With the notation"time" not my colum is meant,
but probably the command
>>>>> "time" in R.
>>>>> 
>>>>> Can you follow my thoughts?
>>>>> 
>>>>> Tobi
>>>>> 
>>>>> 
>>>>> 
>>>>> 
>>>>> 
>>>>> 
>>>>> Am 11.05.2017 um 17:23 schrieb Duncan Murdoch:
>>>>>> Duncan Murdoch
>>>>> ______________________________________________
>>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and
more, see
>>>>> 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.
>>>> ______________________________________________
>>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and
more, see
>>>> 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.
>>>> 
>>> 
>>> 	[[alternative HTML version deleted]]
>>> 
>>> ______________________________________________
>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more,
see
>>> 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.
> 
> 
> 	[[alternative HTML version deleted]]
> 
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> 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.
David Winsemius
Alameda, CA, USA