It is not a R.Net problem, you just try to run a wrong script. Let's run your code on pure R:
> testTs <- c(1, 2, 3)
> tsValue <- ts(testTs, frequency=1, start=c(2010, 1, 1))
> library("forecast")
> arimaFit <- auto.arima(tsValue)
> fcast <- forecast(tsValue, h=36)
> plot(fcast)
Now class(fcast)
equals to forecast
:
> class(fcast)
[1] "forecast"
> as.numeric(fcast)
Error: (list) object cannot be coerced to type 'double'
fcast strucure:
> str(fcast)
List of 11
$ method : chr "Mean"
$ level : num [1:2] 80 95
$ x : Time-Series [1:3] from 2010 to 2012: 1 2 3
$ xname : chr "object"
$ mean : Time-Series [1:36] from 2013 to 2048: 2 2 2 2 2 2 2 2 2 2 ...
$ lower : mts [1:36, 1:2] -0.177 -0.177 -0.177 -0.177 -0.177 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : NULL
.. ..$ : chr [1:2] "80%" "95%"
..- attr(*, "tsp")= num [1:3] 2013 2048 1
..- attr(*, "class")= chr [1:2] "mts" "ts"
$ upper : mts [1:36, 1:2] 4.18 4.18 4.18 4.18 4.18 ...
..- attr(*, "dimnames")=List of 2
.. ..$ : NULL
.. ..$ : chr [1:2] "80%" "95%"
..- attr(*, "tsp")= num [1:3] 2013 2048 1
..- attr(*, "class")= chr [1:2] "mts" "ts"
$ model :List of 4
..$ mu : num 2
..$ mu.se: num 0.577
..$ sd : num 1
..$ call : language meanf(x = object, h = h, level = level, fan = fan)
$ lambda : NULL
$ fitted : Time-Series [1:3] from 2010 to 2012: NA 1 1.5
$ residuals: Time-Series [1:3] from 2010 to 2012: NA 1 1.5
- attr(*, "class")= chr "forecast"