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ML modeling capabilities: Stata vs Gauss

Listed author(s):
  • Armando Sanchez Vargas

    (Institute for Economic Research, UNAM)

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    The main purpose of this work is to discuss Stata’s capability to implement customized likelihood functions compared with Gauss’s. I compare these two high-level programming languages with built-in function libraries and graphic routines. Overall, Stata’s features seem best suited for analyzing specific models of decision-making processes and other microeconometric applications, while Gauss is ideal for analyzing a more ample range of statistical issues based on maximum likelihood estimation. I briefly discuss such modeling capabilities, emphasizing what is still needed and what might be refined.

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    Paper provided by Stata Users Group in its series Mexican Stata Users' Group Meetings 2010 with number 11.

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    Date of creation: 10 Jun 2010
    Handle: RePEc:boc:msug10:11
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