Errors using the holt() - Error in ets: No model able to be fitted

[Glacestrom]

Hello! I received the following error message when using the holt() in the R package forecast. I am running R version 4.0.2. Most other students were able to fix this issue by reinstalling R and R studio with a reliable version or using the other computer. I tried running the code using R version 4.0.5 without success, and I do not have another computer.

input = read.table("6-2.txt",header=TRUE)
attach(input)
CalSales = ts(CalSales, frequency = 12)
library(forecast)
Cal_model = holt(CalSales, h=4)
summary(Cal_model[["model"]])

Error in ets(x, "AAN", alpha = alpha, beta = beta, phi = phi, damped = damped,  : 
  No model able to be fitted
Calls: <Anonymous> ... withVisible -> eval -> eval -> holt -> forecast -> ets
Execution halted

Any help would be greatly appreciated. Thank you in advance!

Table 6.2 gives the monthly calculator demand data for the past two years:
'CalSales'
197
211
203
247
239
269
308
262
258
256
261
288
296
276
305
308
356
393
363
386
443
308
358
384

[robjhyndman]

It should make no difference if you are using an older version of R.

The following code works:

library(forecast)
CalSales <- ts(c(197,211,203,247,239,269,308,262,258,256,261,288,296,276,
                305,308,356,393,363,386,443,308,358,384),
              frequency=12)
Cal_model <- holt(CalSales, h=4)

summary(Cal_model[["model"]])
#> Holt's method 
#> 
#> Call:
#>  holt(y = CalSales, h = 4) 
#> 
#>   Smoothing parameters:
#>     alpha = 1e-04 
#>     beta  = 1e-04 
#> 
#>   Initial states:
#>     l = 199.7736 
#>     b = 7.9699 
#> 
#>   sigma:  33.2374
#> 
#>      AIC     AICc      BIC 
#> 250.0740 253.4073 255.9643 
#> 
#> Training set error measures:
#>                      ME     RMSE      MAE       MPE     MAPE      MASE
#> Training set -0.4254659 30.34144 23.29228 -1.067513 7.490028 0.2374744
#>                   ACF1
#> Training set 0.1562895

^{Created on 2022-05-02 by the reprex package (v2.0.1)}

My guess is that the problem is to do with how you've read in your data. If it has come in as character instead of numerical, this error may appear.