title: In R, auto.arima fails to capture seasonality
body: <p><code>auto.arima()</code> is giving me no seasonal component for my series, even though I can see that there is one present. The function gives me a non seasonal ARIMA model of order (5,0,0). So, when I try to forecast using that model, it just gives the mean. The time series is of daily minimum temperatures in Melbourne, Australia for ten years.</p>
  
  <p><a href="https://i.stack.imgur.com/IdiP0.png" rel="nofollow noreferrer">Click this link to see the data and the auto.arima forecast</a></p>
  
  <p>`</p>
  
  <pre><code>library(readr)
  
  temp &lt;- read_csv("~/Downloads/Melbourne Minimum Temp.csv", 
                   col_types = cols(Date = col_date(format = "%m/%d/%y"), 
                                    Temp = col_number()))
  
  t &lt;- ts(temp$Temp, start = temp$Date\[1], end = temp$Date[nrow(temp)])
  
  auto.arima(t, trace = T)
  </code></pre>
  
  <p>`</p>
  
  <p>Tried using the data as a ts object, as an xts object, and as a vector.</p>