Hey David,
thanks for your reply.
Maybe the time -function is related to the plm-package. In R the
function of time is declared as the following:
Sampling Times of Time Series
Description
|time|creates the vector of times at which a time series was sampled.
|cycle|gives the positions in the cycle of each observation.
|frequency|returns the number of samples per unit time and|deltat|the
time interval between observations (see|ts
<http://127.0.0.1:35865/help/library/stats/help/ts>|).
Usage
time(x, ...)
## Default S3 method:
time(x, offset = 0, ...)
cycle(x, ...)
frequency(x, ...)
deltat(x, ...)
So the error was definitely not caused by a misspelling of an existing
column-name.
Please see attached: _str(R_Test_log_Neu) & library()_
Hope it helps,
Toby
* > **str(R_Test_log_Neu)* Classes ‘tbl_df’, ‘tbl’ and 'data.frame': 132
obs. of 4 variables:
$ town : num 1 1 1 1 1 1 1 1 1 1 ...
$ year : num 1 2 3 4 5 6 7 8 9 10 ...
$ revenue: num 39.9 43.3 44 43.2 39.1 ...
$ supply : num 1 1 1 1 1 1 35 101 181 323 ...
*Pakete in Library* ‘C:/Users/Tobias Christoph/Documents/R/win-library/3.3’:
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Am 12.05.2017 um 22:12 schrieb David Winsemius:
>> On May 12, 2017, at 7:40 AM, Tobias Christoph <s3toc...@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)*
>>
>> 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"?
> It's difficult to respond to these questions. It appears you have either
> created a function named `time` or loaded a package that contains such a
> named function. Several of the origianl responders thought it might be a
> misspelling of an existing column name.
>
> One might guess from the output that `time` represents a linear value from a
> factor-variable across the values of the "year" column. You should probably
> NOT "just square column 'year'". That will probably construct non-orthogonal
> dependencies between "time" and "time"^2. The usual method in ordinary linear
> regression is to use the "poly" function. In your case however the puzzle
> about what that `time` function looks like prevents much further comment.
>
> To support informed discussion on this matter you MUST provide:
>
> --- code that includes all the needed library() calls to load packages or to
> build a time function.
> --- str(R_Test_log_Neu)
>
>
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