[R] Issues whenWorking with Daily Time Series and Generating Forecasts

[Erin Hodgess]

Just figured out the label format!

Erin Hodgess, PhD
mailto: erinm.hodgess using gmail.com


On Mon, Jul 13, 2020 at 6:58 PM Paul Bernal <paulbernal07 using gmail.com> wrote:

> Dear friend, yes,
>
> When I generate the forecasts i want the output to include the original
> series, the fitted vaules and the forecast and I want the x-axis to show
> all dates (both the dates of the historical series plus the future dares in
> YYYY-mm-dd format).
>
> Thank you so much for your kind and valuable help.
>
> Cheers,
>
> Paul
>
>
> El lun., 13 de julio de 2020 7:10 p. m., Erin Hodgess <
> erinm.hodgess using gmail.com> escribió:
>
>> Hi again, Paul!
>>
>> When you are plotting the final product, do you want both the original
>> series, the fitted values, and the forecast, please?
>>
>> I am messing around with your data.
>>
>> Thanks,
>> Erin
>>
>> Erin Hodgess, PhD
>> mailto: erinm.hodgess using gmail.com
>>
>>
>> On Mon, Jul 13, 2020 at 12:41 PM Paul Bernal <paulbernal07 using gmail.com>
>> wrote:
>>
>>> Dear friends, hope you are doing great,
>>>
>>> I am working with a daily time series, the series starts on march,10,
>>> 2020
>>> until july 9th, 2020.
>>>
>>> I would like to know if there is a way to make it a ts object, specifying
>>> the year, month and day with the ts function.
>>>
>>> First, I tried setting the ts object as follows:
>>>
>>> trainingts <- ts(Dataset2$PANCASES, frequency=7)
>>>
>>> but when I plot trainingts, the x-axis (time axis) shows values like 5,
>>> 10,
>>> 15 and not the dates.
>>>
>>> Secondly, I tried doing the following
>>>
>>> trainingts2 <- ts(Dataset2$PANCASES, start=c(2020,3,10), end=c(2020,7,9),
>>> frequency=365.25)
>>>
>>> but with this setup, now the x-axis has extrange values like 2020.006,
>>> 2020.008, etc.
>>>
>>> Now, when generating forecasts with auto.arima function I get extremely
>>> large values for the y-axis, which makes the forecasts look like a flat
>>> line:
>>>
>>> trainingts <- ts(Dataset2$PANCASES, frequency=7)
>>>
>>> ModelArima2 <- auto.arima(trainingts, lambda=0)
>>> ModelArima2For <- forecast(ModelArima2, h=30)
>>> plot(ModelArima2For)
>>>
>>> I am providing the dput() for my dataset below.
>>>
>>> Any help and/or guidance will be greatly appreciated,
>>>
>>> Best regards,
>>>
>>> Paul
>>>
>>>  > dput(Dataset2)
>>> structure(list(DATE = structure(c(18331, 18332, 18333, 18334,
>>> 18335, 18336, 18337, 18338, 18339, 18340, 18341, 18342, 18343,
>>> 18344, 18345, 18346, 18347, 18348, 18349, 18350, 18351, 18352,
>>> 18353, 18354, 18355, 18356, 18357, 18358, 18359, 18360, 18361,
>>> 18362, 18363, 18364, 18365, 18366, 18367, 18368, 18369, 18370,
>>> 18371, 18372, 18373, 18374, 18375, 18376, 18377, 18378, 18379,
>>> 18380, 18381, 18382, 18383, 18384, 18385, 18386, 18387, 18388,
>>> 18389, 18390, 18391, 18392, 18393, 18394, 18395, 18396, 18397,
>>> 18398, 18399, 18400, 18401, 18402, 18403, 18404, 18405, 18406,
>>> 18407, 18408, 18409, 18410, 18411, 18412, 18413, 18414, 18415,
>>> 18416, 18417, 18418, 18419, 18420, 18421, 18422, 18423, 18424,
>>> 18425, 18426, 18427, 18428, 18429, 18430, 18431, 18432, 18433,
>>> 18434, 18435, 18436, 18437, 18438, 18439, 18440, 18441, 18442,
>>> 18443, 18444, 18445, 18446, 18447, 18448, 18449, 18450, 18451,
>>> 18452), class = "Date"), PANCASES = c(1, 8, 11, 27, 36, 43, 55,
>>> 69, 86, 109, 137, 200, 313, 345, 345, 443, 558, 674, 786, 901,
>>> 989, 1181, 1181, 1317, 1475, 1673, 1801, 1988, 2100, 2249, 2528,
>>> 2752, 2974, 3234, 3400, 3472, 3574, 3751, 4016, 4210, 4273, 4467,
>>> 4658, 4821, 5166, 5338, 5538, 5779, 6021, 6021, 6378, 6532, 6720,
>>> 7090, 7090, 7197, 7523, 7731, 7868, 8070, 8282, 8448, 8616, 8783,
>>> 8944, 9118, 9268, 9449, 9606, 9726, 9867, 9977, 10116, 10267,
>>> 10577, 10926, 11183, 11447, 11728, 12131, 12531, 13018, 13463,
>>> 13837, 14095, 14609, 15044, 15463, 16004, 16425, 16854, 17233,
>>> 17889, 18586, 19211, 20059, 21418, 21422, 21962, 22597, 23351,
>>> 24274, 25222, 26030, 26752, 27314, 28030, 29037, 29905, 30658,
>>> 31686, 32785, 33550, 34463, 35237, 35995, 36983, 38149, 39334,
>>> 40291, 41251, 42216)), row.names = c(NA, -122L), class = "data.frame")
>>>
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>>>
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>>

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