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    <title>topic Re: Writing a code for Extended Kalman Filter in SAS Programming</title>
    <link>https://communities.sas.com/t5/SAS-Programming/Writing-a-code-for-Extended-Kalman-Filter/m-p/656627#M196936</link>
    <description>&lt;P&gt;are you using a sas dataset as input and want to use it in SAS data step? If so can you post a sample of this data and explains what aX_t and aY_t &amp;nbsp;mean? Mathematically I understand what these mean. Do you have an expression for f that you can use in a data step. Do you have expressions for error function, state equation and observation equation. If so then you can write it in a sas data step using lawn function in SAS.&lt;/P&gt;</description>
    <pubDate>Wed, 10 Jun 2020 23:48:45 GMT</pubDate>
    <dc:creator>smantha</dc:creator>
    <dc:date>2020-06-10T23:48:45Z</dc:date>
    <item>
      <title>Writing a code for Extended Kalman Filter</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Writing-a-code-for-Extended-Kalman-Filter/m-p/655228#M196622</link>
      <description>&lt;P&gt;Hi, I want to write a code for extended Kalman filter. I know SAS has subroutine such as KALCVF but this subroutine is for a standard linear Kalman filter. The observation equation that I am trying to deal with has non-linear and time-varying coefficients that depends on the value of the previous state variables and observation variables. Specifically, my extended Kalman filter is&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;X_t = a X_t-1 + error (State Equation)&lt;/P&gt;&lt;P&gt;Y_t = f(Y_t-1, X_t-2) X_t-1 + error (Observation Equation),&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;where f is a quadratic function.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;I think there is no way to use subroutine for run this Kalman filter. Probably, I need to write a code from scratch. If anyone had similar experience, please help me with this problem.&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;Thank you&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;&lt;P&gt;&amp;nbsp;&lt;/P&gt;</description>
      <pubDate>Tue, 09 Jun 2020 08:15:54 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Writing-a-code-for-Extended-Kalman-Filter/m-p/655228#M196622</guid>
      <dc:creator>SASingaKorean</dc:creator>
      <dc:date>2020-06-09T08:15:54Z</dc:date>
    </item>
    <item>
      <title>Re: Writing a code for Extended Kalman Filter</title>
      <link>https://communities.sas.com/t5/SAS-Programming/Writing-a-code-for-Extended-Kalman-Filter/m-p/656627#M196936</link>
      <description>&lt;P&gt;are you using a sas dataset as input and want to use it in SAS data step? If so can you post a sample of this data and explains what aX_t and aY_t &amp;nbsp;mean? Mathematically I understand what these mean. Do you have an expression for f that you can use in a data step. Do you have expressions for error function, state equation and observation equation. If so then you can write it in a sas data step using lawn function in SAS.&lt;/P&gt;</description>
      <pubDate>Wed, 10 Jun 2020 23:48:45 GMT</pubDate>
      <guid>https://communities.sas.com/t5/SAS-Programming/Writing-a-code-for-Extended-Kalman-Filter/m-p/656627#M196936</guid>
      <dc:creator>smantha</dc:creator>
      <dc:date>2020-06-10T23:48:45Z</dc:date>
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