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    <title>topic Re: Seasonal Exponential Smoothing in Discussions</title>
    <link>https://community.jmp.com/t5/Discussions/Seasonal-Exponential-Smoothing/m-p/935283#M109105</link>
    <description>&lt;P&gt;I don't see an actual question.&amp;nbsp; My assumption is that your question is, how do something in JMP that can reduce the time/effort it takes to do the steps you specified.&lt;/P&gt;
&lt;P&gt;Most of the steps you mentioned can be handled by setting up a Workflow in JMP, or in just running the steps you indicate, and capturing the scripts that JMP uses for those steps, and then putting it all together in a script.&lt;/P&gt;
&lt;P&gt;However your&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;&lt;SPAN&gt;Analyze \ Specialized Modeling \ Time Series&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;seems to ambiguous to treat in the same way, and too nonspecific to give any advice on how to handle it.&amp;nbsp; Detailing all of the steps you do in the&amp;nbsp;&lt;SPAN&gt;Analyze \ Specialized Modeling \ Time Series steps, along with any diversions you need within the steps would something that needs to be done to allow the Community to evaluate how to automate this.&lt;/SPAN&gt;&amp;nbsp;&lt;/P&gt;</description>
    <pubDate>Fri, 13 Mar 2026 18:11:41 GMT</pubDate>
    <dc:creator>txnelson</dc:creator>
    <dc:date>2026-03-13T18:11:41Z</dc:date>
    <item>
      <title>Seasonal Exponential Smoothing</title>
      <link>https://community.jmp.com/t5/Discussions/Seasonal-Exponential-Smoothing/m-p/935265#M109102</link>
      <description>&lt;P&gt;Have determined data best fits seasonal exponential smoothing forecast model.&amp;nbsp; Doing my yearly forecasting but have hundreds of materials numbers to do my forecast. This is an extremely long and tedious process to do a forecast for each material number.&amp;nbsp;&lt;/P&gt;
&lt;P&gt;Steps&lt;/P&gt;
&lt;P&gt;Set up actual data in excel JMP format.&lt;/P&gt;
&lt;P&gt;First column month YR&lt;/P&gt;
&lt;P&gt;Next 100 columns actual sales data for each material number .&lt;/P&gt;
&lt;P&gt;import data into JMP&lt;/P&gt;
&lt;P&gt;Analyze \ Specialized Modeling \ Time Series&lt;/P&gt;
&lt;P&gt;Add Month YR to X, Time ID&lt;/P&gt;
&lt;P&gt;Add material numbers to Y, Time Series&lt;/P&gt;
&lt;P&gt;Click OK&lt;/P&gt;</description>
      <pubDate>Fri, 13 Mar 2026 15:49:48 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Seasonal-Exponential-Smoothing/m-p/935265#M109102</guid>
      <dc:creator>jtessom</dc:creator>
      <dc:date>2026-03-13T15:49:48Z</dc:date>
    </item>
    <item>
      <title>Re: Seasonal Exponential Smoothing</title>
      <link>https://community.jmp.com/t5/Discussions/Seasonal-Exponential-Smoothing/m-p/935283#M109105</link>
      <description>&lt;P&gt;I don't see an actual question.&amp;nbsp; My assumption is that your question is, how do something in JMP that can reduce the time/effort it takes to do the steps you specified.&lt;/P&gt;
&lt;P&gt;Most of the steps you mentioned can be handled by setting up a Workflow in JMP, or in just running the steps you indicate, and capturing the scripts that JMP uses for those steps, and then putting it all together in a script.&lt;/P&gt;
&lt;P&gt;However your&amp;nbsp;&lt;/P&gt;
&lt;P&gt;&amp;nbsp; &amp;nbsp; &amp;nbsp;&lt;SPAN&gt;Analyze \ Specialized Modeling \ Time Series&lt;/SPAN&gt;&lt;/P&gt;
&lt;P&gt;seems to ambiguous to treat in the same way, and too nonspecific to give any advice on how to handle it.&amp;nbsp; Detailing all of the steps you do in the&amp;nbsp;&lt;SPAN&gt;Analyze \ Specialized Modeling \ Time Series steps, along with any diversions you need within the steps would something that needs to be done to allow the Community to evaluate how to automate this.&lt;/SPAN&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Fri, 13 Mar 2026 18:11:41 GMT</pubDate>
      <guid>https://community.jmp.com/t5/Discussions/Seasonal-Exponential-Smoothing/m-p/935283#M109105</guid>
      <dc:creator>txnelson</dc:creator>
      <dc:date>2026-03-13T18:11:41Z</dc:date>
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