Hello everyone,
So this is my first post to this list, I'm trying to fit an Arima (2,0,0)
model and I think a drift term would help but I'm getting an error term
when I'm trying to include it. Here is my data:
-6.732172338
-2.868884273
-5.371585089
-6.512740463
-4.171062657
-5.738499071
-3.343947176
-1.944879508
-5.464109272
-3.189183392
-3.684700232
-2.168303451
-2.329837082
-0.761979236
-2.189025304
1.094238807
-4.812300745
0.784198777
-1.567075922
0.143963653
1.131119051
2.899746353
-0.498719993
3.121623505 I created a time series object with 24 annual observations. I
didn't include dates because there isn't an observation for every year.
tsdata<-ts(read.csv("...\\Pre2001LaunchDateTraining.csv"), start =
c(1,1),
end = c(24,1), frequency = 1) I then created a time series object using the
Arima() function. fitdata <- Arima(tsdata,c(2,0,0),include.drift =
"true")
After executing I get this error: Error in (order[2] + seasonal$order[2]) >
1 & include.drift: operations are possible only for numeric, logical or
complex types Traceback: 1. Arima(tsdata, c(2, 0, 0), include.drift =
"true")
Any help would be greatly appreciated!
[[alternative HTML version deleted]]
Please start by reading and following the posting guide linked at the bottom of this email. In particular: 1) Post in **plain text** on this plain text list so we don't get the mangled html of your post. 2) Tell us what package Arima() is in. Cheers, Bert Gunter On Thu, May 9, 2019 at 2:27 PM Michael Howell <mchowell2 at gmail.com> wrote:> Hello everyone, > So this is my first post to this list, I'm trying to fit an Arima (2,0,0) > model and I think a drift term would help but I'm getting an error term > when I'm trying to include it. Here is my data: > > -6.732172338 > -2.868884273 > -5.371585089 > -6.512740463 > -4.171062657 > -5.738499071 > -3.343947176 > -1.944879508 > -5.464109272 > -3.189183392 > -3.684700232 > -2.168303451 > -2.329837082 > -0.761979236 > -2.189025304 > 1.094238807 > -4.812300745 > 0.784198777 > -1.567075922 > 0.143963653 > 1.131119051 > 2.899746353 > -0.498719993 > 3.121623505 I created a time series object with 24 annual observations. I > didn't include dates because there isn't an observation for every year. > > tsdata<-ts(read.csv("...\\Pre2001LaunchDateTraining.csv"), start = c(1,1), > end = c(24,1), frequency = 1) I then created a time series object using the > Arima() function. fitdata <- Arima(tsdata,c(2,0,0),include.drift = "true") > After executing I get this error: Error in (order[2] + seasonal$order[2]) > > 1 & include.drift: operations are possible only for numeric, logical or > complex types Traceback: 1. Arima(tsdata, c(2, 0, 0), include.drift > "true") > Any help would be greatly appreciated! > > [[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]]
In future, always cc the list (unless it's personal,which this isn't). I have done so here. As I am largely ignorant on the subject matter, others will have to help, which is why you should cc the list. Cheers, Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Thu, May 9, 2019 at 3:49 PM Michael Howell <mchowell2 at gmail.com> wrote:> I apologize for that. The Arima() function that I'm trying to use comes > from the forecast package. I created a time series object using the above > 24 observations. The initial model I created doesn't seem to perform so > well so I thought a drift term might fit the data better. I used the > following code to create the time series object: > > tsdata<- ts(data, start = c(1,1), end = c(24,1), frequency = 1) > > > Where* data* is the dataframe that contains the initial 24 observations. > I then used the following code to try to create the model: > > fitdata <- Arima(tsdata,c(2,0,0),include.drift="true") >> > > After doing this I obtained the following error message: > > Error in (order[2] + seasonal$order[2]) > 1 & include.drift: operations >> are possible only for numeric, logical or complex types >> Traceback: >> >> 1. Arima(tsdata, c(2, 0, 0), include.drift = "true") > > > I hope this is more clear. > > On Thu, May 9, 2019 at 4:39 PM Bert Gunter <bgunter.4567 at gmail.com> wrote: > >> Please start by reading and following the posting guide linked at the >> bottom of this email. In particular: >> >> 1) Post in **plain text** on this plain text list so we don't get the >> mangled html of your post. >> >> 2) Tell us what package Arima() is in. >> >> Cheers, >> Bert Gunter >> >> >> >> >> On Thu, May 9, 2019 at 2:27 PM Michael Howell <mchowell2 at gmail.com> >> wrote: >> >>> Hello everyone, >>> So this is my first post to this list, I'm trying to fit an Arima (2,0,0) >>> model and I think a drift term would help but I'm getting an error term >>> when I'm trying to include it. Here is my data: >>> >>> -6.732172338 >>> -2.868884273 >>> -5.371585089 >>> -6.512740463 >>> -4.171062657 >>> -5.738499071 >>> -3.343947176 >>> -1.944879508 >>> -5.464109272 >>> -3.189183392 >>> -3.684700232 >>> -2.168303451 >>> -2.329837082 >>> -0.761979236 >>> -2.189025304 >>> 1.094238807 >>> -4.812300745 >>> 0.784198777 >>> -1.567075922 >>> 0.143963653 >>> 1.131119051 >>> 2.899746353 >>> -0.498719993 >>> 3.121623505 I created a time series object with 24 annual observations. I >>> didn't include dates because there isn't an observation for every year. >>> >>> tsdata<-ts(read.csv("...\\Pre2001LaunchDateTraining.csv"), start >>> c(1,1), >>> end = c(24,1), frequency = 1) I then created a time series object using >>> the >>> Arima() function. fitdata <- Arima(tsdata,c(2,0,0),include.drift >>> "true") >>> After executing I get this error: Error in (order[2] + >>> seasonal$order[2]) > >>> 1 & include.drift: operations are possible only for numeric, logical or >>> complex types Traceback: 1. Arima(tsdata, c(2, 0, 0), include.drift >>> "true") >>> Any help would be greatly appreciated! >>> >>> [[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]]
Hello,
This is just a typo, in R logical values ("true) are not character
strings. You must pass FALSE (the default, can be omited) or TRUE.
fitdata <- Arima(tsdata, c(2, 0, 0), include.drift = TRUE)
From the help page ?logical
Details
TRUE and FALSE are reserved words denoting logical constants in the R
language, whereas T and F are global variables whose initial values set
to these. All four are logical(1) vectors.
Hope this helps,
Rui Barradas
?s 00:26 de 10/05/19, Bert Gunter escreveu:> In future, always cc the list (unless it's personal,which this
isn't). I
> have done so here. As I am largely ignorant on the subject matter, others
> will have to help, which is why you should cc the list.
>
> Cheers,
> Bert Gunter
>
> "The trouble with having an open mind is that people keep coming along
and
> sticking things into it."
> -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip
)
>
>
> On Thu, May 9, 2019 at 3:49 PM Michael Howell <mchowell2 at
gmail.com> wrote:
>
>> I apologize for that. The Arima() function that I'm trying to use
comes
>> from the forecast package. I created a time series object using the
above
>> 24 observations. The initial model I created doesn't seem to
perform so
>> well so I thought a drift term might fit the data better. I used the
>> following code to create the time series object:
>>
>> tsdata<- ts(data, start = c(1,1), end = c(24,1), frequency = 1)
>>
>>
>> Where* data* is the dataframe that contains the initial 24
observations.
>> I then used the following code to try to create the model:
>>
>> fitdata <- Arima(tsdata,c(2,0,0),include.drift="true")
>>>
>>
>> After doing this I obtained the following error message:
>>
>> Error in (order[2] + seasonal$order[2]) > 1 & include.drift:
operations
>>> are possible only for numeric, logical or complex types
>>> Traceback:
>>>
>>> 1. Arima(tsdata, c(2, 0, 0), include.drift = "true")
>>
>>
>> I hope this is more clear.
>>
>> On Thu, May 9, 2019 at 4:39 PM Bert Gunter <bgunter.4567 at
gmail.com> wrote:
>>
>>> Please start by reading and following the posting guide linked at
the
>>> bottom of this email. In particular:
>>>
>>> 1) Post in **plain text** on this plain text list so we don't
get the
>>> mangled html of your post.
>>>
>>> 2) Tell us what package Arima() is in.
>>>
>>> Cheers,
>>> Bert Gunter
>>>
>>>
>>>
>>>
>>> On Thu, May 9, 2019 at 2:27 PM Michael Howell <mchowell2 at
gmail.com>
>>> wrote:
>>>
>>>> Hello everyone,
>>>> So this is my first post to this list, I'm trying to fit an
Arima (2,0,0)
>>>> model and I think a drift term would help but I'm getting
an error term
>>>> when I'm trying to include it. Here is my data:
>>>>
>>>> -6.732172338
>>>> -2.868884273
>>>> -5.371585089
>>>> -6.512740463
>>>> -4.171062657
>>>> -5.738499071
>>>> -3.343947176
>>>> -1.944879508
>>>> -5.464109272
>>>> -3.189183392
>>>> -3.684700232
>>>> -2.168303451
>>>> -2.329837082
>>>> -0.761979236
>>>> -2.189025304
>>>> 1.094238807
>>>> -4.812300745
>>>> 0.784198777
>>>> -1.567075922
>>>> 0.143963653
>>>> 1.131119051
>>>> 2.899746353
>>>> -0.498719993
>>>> 3.121623505 I created a time series object with 24 annual
observations. I
>>>> didn't include dates because there isn't an observation
for every year.
>>>>
>>>>
tsdata<-ts(read.csv("...\\Pre2001LaunchDateTraining.csv"), start
>>>> c(1,1),
>>>> end = c(24,1), frequency = 1) I then created a time series
object using
>>>> the
>>>> Arima() function. fitdata <-
Arima(tsdata,c(2,0,0),include.drift >>>> "true")
>>>> After executing I get this error: Error in (order[2] +
>>>> seasonal$order[2]) >
>>>> 1 & include.drift: operations are possible only for
numeric, logical or
>>>> complex types Traceback: 1. Arima(tsdata, c(2, 0, 0),
include.drift >>>> "true")
>>>> Any help would be greatly appreciated!
>>>>
>>>> [[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.
>