Issues whenWorking with Daily Time Series and Generating Forecasts

Hi Paul

Have you looked at the xts or zoo packages, please?

They work very well on daily series.

Thanks,
Erin

On Mon, Jul 13, 2020 at 12:41 PM Paul Bernal <paulbernal07 at 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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--
Erin Hodgess, PhD
mailto: erinm.hodgess at gmail.com