title: QuantileRegression ValueError: operands could not be broadcast together with shapes
body: <p>I am trying to forecast my target variable using Quantile Regression in Python.</p>
  <p>The data I am considering for training and validation is from period 2015 Oct -2017 Dec 31st.</p>
  <p>Now the model has developed,Im trying to forecast values for 2018 Jan, which throws the following error:</p>
  <blockquote>
  <p>ValueError: operands could not be broadcast together with shapes (34,) (33,)</p>
  </blockquote>
  <pre><code>mod = smf.quantreg('ASBCU_SUM~Month+Year+WeekofMonth+DayNum+isHoliday+PCOP_CS+PCOP_LS+PCOP_IFS+PCOP_LSS+PCOP_FSS+PCOP_FS+DayOfWeek_6+DayOfWeek_5+DayOfWeek_2+DayOfWeek_7+DayOfWeek_3+DayOfWeek_4',dfTrainingData)
  
  res = mod.fit(q=0.8)
  </code></pre>
  <p>If I check,the error comes from quantile regression.py file inside statmodels.</p>
  <pre><code>diff = np.max(np.abs(beta - beta0))
  </code></pre>
  <p>I have gone through similar posts on stack overflow,which recommends to check the data type of target variable being numerical or not.
  This is the dtype of the variables:</p>
  <blockquote>
  <p>ASBCU_SUM: int64</p>
  <p>Month: category</p>
  <p>Year: category</p>
  <p>WeekofMonth: category</p>
  <p>isHoliday: int64</p>
  <p>DayNum: int32</p>
  <p>PCOP_SUM: int64</p>
  <p>PCOP_CS: int64</p>
  <p>PCOP_LS: int64</p>
  <p>PCOP_IFS: int64</p>
  <p>PCOP_LSS: int64</p>
  <p>PCOP_FS: int64</p>
  <p>PCOP_FSS: int64</p>
  <p>DayOfWeek_3: float64</p>
  <p>DayOfWeek_2: float64</p>
  <p>DayOfWeek_5: float64</p>
  <p>DayOfWeek_7: float64</p>
  <p>DayOfWeek_4: float64</p>
  <p>DayOfWeek_6: float64</p>
  </blockquote>
  <p>The datatypes are same while developing the model using 2015-2017 data as well.</p>
  <p>I really appreciate any help..</p>