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    <title>topic Re: impute time series with seasonality in SAS Forecasting and Econometrics</title>
    <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/impute-time-series-with-seasonality/m-p/338532#M2187</link>
    <description>&lt;P&gt;Thank you! the results look good!&lt;/P&gt;</description>
    <pubDate>Mon, 06 Mar 2017 18:45:22 GMT</pubDate>
    <dc:creator>A_S</dc:creator>
    <dc:date>2017-03-06T18:45:22Z</dc:date>
    <item>
      <title>impute time series with seasonality</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/impute-time-series-with-seasonality/m-p/338457#M2182</link>
      <description>&lt;P&gt;I have 50000 time series with seasonal trends and missing values. I would like to use seasonality to impute the missing values.&lt;/P&gt;&lt;P&gt;Please let me know if SAS has a proceedure for this.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;The data is output from PROC TIMESERIES (interval = week).&lt;/P&gt;&lt;P&gt;The data covers 15 or 16 years (depends on which time series).&lt;/P&gt;&lt;P&gt;The seasonal patterns are all one year long (a period of one year, and correspond to spring, summer, autumn and winter).&lt;/P&gt;&lt;P&gt;Some of the gaps cover an entire season for a year, but other years have the corresponding season data (summer 2015 is missing; but summer 2014 and summer 2016 are not missing).&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Because of the missing seasons, I am unsure if PROC EXPAND's methods will give reasonable results.&lt;/P&gt;&lt;P&gt;Would PROC MI's MCMC give solid results?&lt;/P&gt;&lt;P&gt;Initially, I used PROC HPSUMMARY to find monthly medians and imputed. Unfortunately, a collaborator objects to the four-week stair patterns.&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you!&lt;/P&gt;</description>
      <pubDate>Mon, 06 Mar 2017 14:53:14 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/impute-time-series-with-seasonality/m-p/338457#M2182</guid>
      <dc:creator>A_S</dc:creator>
      <dc:date>2017-03-06T14:53:14Z</dc:date>
    </item>
    <item>
      <title>Re: impute time series with seasonality</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/impute-time-series-with-seasonality/m-p/338481#M2184</link>
      <description>&lt;P&gt;One approach you can consider is to use a forecasting model to impute the historical missing values. For example, you can use PROC ESM with method = WINTERS to forecast the series. You will get not only the furture forecasts but also in-sample fit for the entire history including the missing value periods. You can use the in-sample fit to imput the historical missing values.&lt;/P&gt;
&lt;P&gt;Alex&lt;/P&gt;</description>
      <pubDate>Mon, 06 Mar 2017 15:56:29 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/impute-time-series-with-seasonality/m-p/338481#M2184</guid>
      <dc:creator>alexchien</dc:creator>
      <dc:date>2017-03-06T15:56:29Z</dc:date>
    </item>
    <item>
      <title>Re: impute time series with seasonality</title>
      <link>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/impute-time-series-with-seasonality/m-p/338532#M2187</link>
      <description>&lt;P&gt;Thank you! the results look good!&lt;/P&gt;</description>
      <pubDate>Mon, 06 Mar 2017 18:45:22 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Forecasting-and-Econometrics/impute-time-series-with-seasonality/m-p/338532#M2187</guid>
      <dc:creator>A_S</dc:creator>
      <dc:date>2017-03-06T18:45:22Z</dc:date>
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