Partially the trouble is that the zoo time series is then translated
into a ts object by auto.arima.
In doing so, the series along a regular time grid and some missing
data appear.
To fix this, I should replace each NA with the previous non-NA value.
This is easy enough and the series exhibits som
> On Jan 29, 2016, at 12:59 PM, Lorenzo Isella wrote:
>
> Dear All,
> I am puzzled and probably I am misunderstanding something.
> Please consider the snippet at the end of the email.
> We see a time series that has clearly some pattern (essentially, it is
> an account where a salary is regularl
Thanks,
But something fishy is going on.
The fitted time series is full of missing values, whereas the original
tt object does not have any.
I suppose that in trying to fit the time series defined on an
irregular time grid, some problem arises inside the auto.arima
function.
Lorenzo
On Fri, Jan
Dear All,
I am puzzled and probably I am misunderstanding something.
Please consider the snippet at the end of the email.
We see a time series that has clearly some pattern (essentially, it is
an account where a salary is regularly paid followed by some
expenses).
However the output of the auto.ar
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