title: ACF and PACF interpretation
body: <p>I have difficulty reading the ACF and PACF plots and determining the lag for the model. </p>
  
  <p>I am forecasting the  daily electricity load data which looks as follows:</p>
  
  <pre><code>           date  temperature   load   weekday month weekend day
  1    2010-01-01         -28 256131       5    01       0   1
  2    2010-01-02         -24 277749       6    01       1   2
  3    2010-01-03         -53 264166       0    01       1   3
  4    2010-01-04         -42 319847       1    01       0   4
  5    2010-01-05         -17 321376       2    01       0   5
  </code></pre>
  
  <p>To get the ACF and PACF I have performed the following: </p>
  
  <pre><code>#create time series     
  NLdailyts &lt;- ts(NLdaily$load, frequency =365.25, start = c(2010,1,1))
  #difference time series 
  NLdailytsdiff &lt;- diff(NLdailyts,differences = 365.25)
  
  #ACF plot in days 
  ## Calculate, but not plot, acf
  acfpl&lt;- acf(NLdailytsdiff, plot = FALSE)
  ## Transform the lags from years to days 
  acfpl$lag &lt;- acfpl$lag * 365.25
  ## Plot the acf 
  plot(acfpl, xlab="Lag (days)")
  
  #PACF plot in days 
  ## Calculate, but not plot, acf
  pacfpl&lt;- pacf(NLdailytsdiff, plot = FALSE)
  ## Transform the lags from years to days 
  pacfpl$lag &lt;- pacfpl$lag * 365
  ## Plot the acf 
  plot(pacfpl, xlab="Lag (days)")
  </code></pre>
  
  <p>Which gives me the following plots: </p>
  
  <p><a href="https://i.stack.imgur.com/wdGQT.png" rel="nofollow noreferrer">ACF</a> and <a href="https://i.stack.imgur.com/rbzYu.png" rel="nofollow noreferrer">PACF</a></p>
  
  <p>EDIT: I have found out that alternating positive and negative values mean that the data is stationary.</p>
  
  <p>How should I interpret both? And which lag should I use?</p>