Object not found error in Forecast Packagecompatibility issue of magrittr and arima in RFind the version of an installed npm packageForecast accuracy: no MASE with two vectors as argumentsError with forecast.Arima with xregForecasting ARIMA with xregError in meanf - unused argumentHow to create a forecast object in RQ: R NNETAR external regressors incorporationR forecast.holtwinters in forecast package not foundFourier transform for daily & weekly dataarima xreg argument error caused by column name in data frame
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Object not found error in Forecast Package
compatibility issue of magrittr and arima in RFind the version of an installed npm packageForecast accuracy: no MASE with two vectors as argumentsError with forecast.Arima with xregForecasting ARIMA with xregError in meanf - unused argumentHow to create a forecast object in RQ: R NNETAR external regressors incorporationR forecast.holtwinters in forecast package not foundFourier transform for daily & weekly dataarima xreg argument error caused by column name in data frame
.everyoneloves__top-leaderboard:empty,.everyoneloves__mid-leaderboard:empty,.everyoneloves__bot-mid-leaderboard:empty margin-bottom:0;
I'm working with the forecast package (version 8.5) in R (version 3.5.3), attempting to do some ARIMA forecasting using the magnificent auto.arima() function.
When running this function, I always receive an error code which says,
"Error in eval(expr, p) : object 'fitxreg' not found". I have already tried debugging, and I wasn't able to figure out exactly what the problem was, but when I revert back to forecast 8.4, this block of code works without an issue.
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
I would expect this to return a forecast object from auto.arima() that does not use external regressors (note that both fitxreg and forxreg are NULL). However, I simply get the error described above.
Any help is greatly appreciated!
r package forecast
asked Mar 26 at 19:30
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
add a comment |
I'm working with the forecast package (version 8.5) in R (version 3.5.3), attempting to do some ARIMA forecasting using the magnificent auto.arima() function.
When running this function, I always receive an error code which says,
"Error in eval(expr, p) : object 'fitxreg' not found". I have already tried debugging, and I wasn't able to figure out exactly what the problem was, but when I revert back to forecast 8.4, this block of code works without an issue.
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
I would expect this to return a forecast object from auto.arima() that does not use external regressors (note that both fitxreg and forxreg are NULL). However, I simply get the error described above.
Any help is greatly appreciated!
r package forecast
asked Mar 26 at 19:30
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
add a comment |
I'm working with the forecast package (version 8.5) in R (version 3.5.3), attempting to do some ARIMA forecasting using the magnificent auto.arima() function.
When running this function, I always receive an error code which says,
"Error in eval(expr, p) : object 'fitxreg' not found". I have already tried debugging, and I wasn't able to figure out exactly what the problem was, but when I revert back to forecast 8.4, this block of code works without an issue.
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
I would expect this to return a forecast object from auto.arima() that does not use external regressors (note that both fitxreg and forxreg are NULL). However, I simply get the error described above.
Any help is greatly appreciated!
r package forecast
asked Mar 26 at 19:30
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
I'm working with the forecast package (version 8.5) in R (version 3.5.3), attempting to do some ARIMA forecasting using the magnificent auto.arima() function.
When running this function, I always receive an error code which says,
"Error in eval(expr, p) : object 'fitxreg' not found". I have already tried debugging, and I wasn't able to figure out exactly what the problem was, but when I revert back to forecast 8.4, this block of code works without an issue.
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
I would expect this to return a forecast object from auto.arima() that does not use external regressors (note that both fitxreg and forxreg are NULL). However, I simply get the error described above.
Any help is greatly appreciated!
r package forecast
r package forecast
asked Mar 26 at 19:30
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
asked Mar 26 at 19:30
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
asked Mar 26 at 19:30
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
asked Mar 26 at 19:30
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
asked Mar 26 at 19:30
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
1799 bronze badges
add a comment |
add a comment |
2 Answers
2
active
oldest
votes
Solution
We can add a check to see if fitxreg is NULL or not
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
if(missing(fitxreg))
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = NULL, lambda = 'auto', allowmean = TRUE)
else
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Returns:
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
Solution if you don't mind setting a variable to your global environment,
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fitxreg <<- fitxreg
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
answered Mar 26 at 19:40
Hector HaffendenHector Haffenden
9244 silver badges16 bronze badges
That definitely works, but is there anyway to handle this issue without setting a variable in the global environment? Thank you for your help!
– BurlyPotatoMan
Mar 26 at 19:45
Is this more appropriate? @BurlyPotatoMan
– Hector Haffenden
Mar 26 at 19:55
Yes! Thank you! I just posted a solution that does the same thing, just with less code. Thank you for the help!
– BurlyPotatoMan
Mar 26 at 20:03
@BurlyPotatoMan No worries, it was an interesting problem, consider accepting the answer (green tick to the upper left of the answer), if it answered your question.
– Hector Haffenden
Mar 26 at 20:05
add a comment |
Got it!
The issue is that the fit object contains the name of the external regressor as 'fitxreg' and when forecast() goes to look for 'fitxreg', it finds nothing. The following update to the code now produces a forecast. Thanks to Hector for the clue as to what was going on!
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fit <- auto.arima(AirPassengers[1:87], seasonal = FALSE, xreg = fitxreg, lambda = 'auto',
allowmean = TRUE)
if(is.null(fitxreg))
fit$call$xreg <- NULL
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
answered Mar 26 at 20:02
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
add a comment |
Your Answer
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2 Answers
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Solution
We can add a check to see if fitxreg is NULL or not
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
if(missing(fitxreg))
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = NULL, lambda = 'auto', allowmean = TRUE)
else
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Returns:
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
Solution if you don't mind setting a variable to your global environment,
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fitxreg <<- fitxreg
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
answered Mar 26 at 19:40
Hector HaffendenHector Haffenden
9244 silver badges16 bronze badges
That definitely works, but is there anyway to handle this issue without setting a variable in the global environment? Thank you for your help!
– BurlyPotatoMan
Mar 26 at 19:45
Is this more appropriate? @BurlyPotatoMan
– Hector Haffenden
Mar 26 at 19:55
Yes! Thank you! I just posted a solution that does the same thing, just with less code. Thank you for the help!
– BurlyPotatoMan
Mar 26 at 20:03
@BurlyPotatoMan No worries, it was an interesting problem, consider accepting the answer (green tick to the upper left of the answer), if it answered your question.
– Hector Haffenden
Mar 26 at 20:05
add a comment |
Solution
We can add a check to see if fitxreg is NULL or not
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
if(missing(fitxreg))
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = NULL, lambda = 'auto', allowmean = TRUE)
else
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Returns:
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
Solution if you don't mind setting a variable to your global environment,
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fitxreg <<- fitxreg
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
answered Mar 26 at 19:40
Hector HaffendenHector Haffenden
9244 silver badges16 bronze badges
That definitely works, but is there anyway to handle this issue without setting a variable in the global environment? Thank you for your help!
– BurlyPotatoMan
Mar 26 at 19:45
Is this more appropriate? @BurlyPotatoMan
– Hector Haffenden
Mar 26 at 19:55
Yes! Thank you! I just posted a solution that does the same thing, just with less code. Thank you for the help!
– BurlyPotatoMan
Mar 26 at 20:03
@BurlyPotatoMan No worries, it was an interesting problem, consider accepting the answer (green tick to the upper left of the answer), if it answered your question.
– Hector Haffenden
Mar 26 at 20:05
add a comment |
Solution
We can add a check to see if fitxreg is NULL or not
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
if(missing(fitxreg))
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = NULL, lambda = 'auto', allowmean = TRUE)
else
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Returns:
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
Solution if you don't mind setting a variable to your global environment,
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fitxreg <<- fitxreg
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
answered Mar 26 at 19:40
Hector HaffendenHector Haffenden
9244 silver badges16 bronze badges
Solution
We can add a check to see if fitxreg is NULL or not
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
if(missing(fitxreg))
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = NULL, lambda = 'auto', allowmean = TRUE)
else
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Returns:
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
Solution if you don't mind setting a variable to your global environment,
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fitxreg <<- fitxreg
fit <- auto.arima(AirPassengers[1:87],
seasonal = FALSE,
xreg = fitxreg, lambda = 'auto', allowmean = TRUE)
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
Point Forecast Lo 80 Hi 80 Lo 95 Hi 95
88 320.8124 278.8410 370.7503 259.3371 401.0221
89 310.9559 254.0070 384.2721 229.0197 431.6157
90 301.5867 239.6709 384.1640 213.1853 439.0395
answered Mar 26 at 19:40
Hector HaffendenHector Haffenden
9244 silver badges16 bronze badges
edited Mar 26 at 19:53
answered Mar 26 at 19:40
Hector HaffendenHector Haffenden
9244 silver badges16 bronze badges
answered Mar 26 at 19:40
Hector HaffendenHector Haffenden
9244 silver badges16 bronze badges
answered Mar 26 at 19:40
Hector HaffendenHector Haffenden
9244 silver badges16 bronze badges
9244 silver badges16 bronze badges
That definitely works, but is there anyway to handle this issue without setting a variable in the global environment? Thank you for your help!
– BurlyPotatoMan
Mar 26 at 19:45
Is this more appropriate? @BurlyPotatoMan
– Hector Haffenden
Mar 26 at 19:55
Yes! Thank you! I just posted a solution that does the same thing, just with less code. Thank you for the help!
– BurlyPotatoMan
Mar 26 at 20:03
@BurlyPotatoMan No worries, it was an interesting problem, consider accepting the answer (green tick to the upper left of the answer), if it answered your question.
– Hector Haffenden
Mar 26 at 20:05
add a comment |
That definitely works, but is there anyway to handle this issue without setting a variable in the global environment? Thank you for your help!
– BurlyPotatoMan
Mar 26 at 19:45
Is this more appropriate? @BurlyPotatoMan
– Hector Haffenden
Mar 26 at 19:55
Yes! Thank you! I just posted a solution that does the same thing, just with less code. Thank you for the help!
– BurlyPotatoMan
Mar 26 at 20:03
@BurlyPotatoMan No worries, it was an interesting problem, consider accepting the answer (green tick to the upper left of the answer), if it answered your question.
– Hector Haffenden
Mar 26 at 20:05
That definitely works, but is there anyway to handle this issue without setting a variable in the global environment? Thank you for your help!
– BurlyPotatoMan
Mar 26 at 19:45
That definitely works, but is there anyway to handle this issue without setting a variable in the global environment? Thank you for your help!
– BurlyPotatoMan
Mar 26 at 19:45
Is this more appropriate? @BurlyPotatoMan
– Hector Haffenden
Mar 26 at 19:55
Is this more appropriate? @BurlyPotatoMan
– Hector Haffenden
Mar 26 at 19:55
Yes! Thank you! I just posted a solution that does the same thing, just with less code. Thank you for the help!
– BurlyPotatoMan
Mar 26 at 20:03
Yes! Thank you! I just posted a solution that does the same thing, just with less code. Thank you for the help!
– BurlyPotatoMan
Mar 26 at 20:03
@BurlyPotatoMan No worries, it was an interesting problem, consider accepting the answer (green tick to the upper left of the answer), if it answered your question.
– Hector Haffenden
Mar 26 at 20:05
@BurlyPotatoMan No worries, it was an interesting problem, consider accepting the answer (green tick to the upper left of the answer), if it answered your question.
– Hector Haffenden
Mar 26 at 20:05
add a comment |
Got it!
The issue is that the fit object contains the name of the external regressor as 'fitxreg' and when forecast() goes to look for 'fitxreg', it finds nothing. The following update to the code now produces a forecast. Thanks to Hector for the clue as to what was going on!
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fit <- auto.arima(AirPassengers[1:87], seasonal = FALSE, xreg = fitxreg, lambda = 'auto',
allowmean = TRUE)
if(is.null(fitxreg))
fit$call$xreg <- NULL
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
answered Mar 26 at 20:02
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
add a comment |
Got it!
The issue is that the fit object contains the name of the external regressor as 'fitxreg' and when forecast() goes to look for 'fitxreg', it finds nothing. The following update to the code now produces a forecast. Thanks to Hector for the clue as to what was going on!
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fit <- auto.arima(AirPassengers[1:87], seasonal = FALSE, xreg = fitxreg, lambda = 'auto',
allowmean = TRUE)
if(is.null(fitxreg))
fit$call$xreg <- NULL
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
answered Mar 26 at 20:02
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
add a comment |
Got it!
The issue is that the fit object contains the name of the external regressor as 'fitxreg' and when forecast() goes to look for 'fitxreg', it finds nothing. The following update to the code now produces a forecast. Thanks to Hector for the clue as to what was going on!
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fit <- auto.arima(AirPassengers[1:87], seasonal = FALSE, xreg = fitxreg, lambda = 'auto',
allowmean = TRUE)
if(is.null(fitxreg))
fit$call$xreg <- NULL
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
answered Mar 26 at 20:02
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
Got it!
The issue is that the fit object contains the name of the external regressor as 'fitxreg' and when forecast() goes to look for 'fitxreg', it finds nothing. The following update to the code now produces a forecast. Thanks to Hector for the clue as to what was going on!
arimaIssue <- function(fitxreg = NULL, forxreg = NULL)
library(forecast)
fit <- auto.arima(AirPassengers[1:87], seasonal = FALSE, xreg = fitxreg, lambda = 'auto',
allowmean = TRUE)
if(is.null(fitxreg))
fit$call$xreg <- NULL
fcast <- forecast(fit, xreg = forxreg, h = 3)
return(fcast)
arimaIssue()
answered Mar 26 at 20:02
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
answered Mar 26 at 20:02
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
answered Mar 26 at 20:02
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
answered Mar 26 at 20:02
BurlyPotatoManBurlyPotatoMan
1799 bronze badges
1799 bronze badges
add a comment |
add a comment |
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Required, but never shown
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StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function ()
StackExchange.helpers.onClickDraftSave('#login-link');
);
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
