Not quite sure what you mean with "dealing with NAs in use-specific code".
Some functions handle these automatically, like lm(). If you write your own code, and want to handle NA-s somehow, you have to implement such checks yourself. You may also use the "complete.cases" function (but that does not detect Inf-s). Typically your own handling means excluding NA-s in one way or another as most of the math operations are not defined on these. Cheers, Ott On Wed, Sep 9, 2015 at 12:03 PM, Olu Ola via R-help <r-help@r-project.org> wrote: > Hello, > I have a dataset that have a couple of missing values and I DO NOT want to > delete the observations with the missing values. I have read about > na.action in dealing with missing values but I do not know how it applies > to user-specific written code. > > Is there a code you can use with your dataset so that subsequent analysis > will automatically detect missing values? > > The following are some of the things I will be doing so that you can > advice me appropriately > > Computing OLS estimates using the matrix approach > Write objective and gradient function subroutines which will now be used > in the Optimx for nonlinear optimization. > > Thank you > > ______________________________________________ > R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > -- Ott Toomet Visiting Researcher School of Information Mary Gates Hall, Suite 310 University of Washington Seattle, WA 98195 [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.