arima - Forecasting 5 Day Sales -


i have daily sales data between 2013-02-18 2017-02-12 has 4 days of data missing (all xmases on 25th of each year). these holidays have sale volume of zero. my purpose understand how staff store upcoming week short-term predicting sales next 5-7 days worth of data.

i start setting data time series: 

ts <- ts(mydata, frequency = 365)

and initial analysis through decomposition:

decomposition of daily data between 2013-02-18 2017-02-12

this seems show have declining sales trend, there seasonality, if i'm not mistaken. so, start forecast implementation, fit arima model first 2 years worth of data doing:

fit <- auto.arima(ts[1:730], stepwise = false, approximation = false)  series: ts[1:730]  arima(4,1,1)                      coefficients:          ar1      ar2      ar3      ar4      ma1       0.3638  -0.2290  -0.1451  -0.2075  -0.8958 s.e.  0.0413   0.0388   0.0388   0.0398   0.0241  sigma^2 estimated 15424930:  log likelihood=-7068.67 aic=14149.33   aicc=14149.45   bic=14176.88

this model doesn't seem right me, because not include seasonality. know have enough data. rob hyndman's blog said try using ets showed no seasonality. not understanding data series or forecasting methodology?

i've re-asked question more appropriately in stats exchange forums. please close question here in stackexchange me?

the questions here. https://stats.stackexchange.com/questions/295012/forecast-5-7-day-sales


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