<div dir="ltr"><div class="gmail_default" style="font-size:small">You may also look at the "where" function, which is a little more flexible than "ind".</div><div class="gmail_default" style="font-size:small"><br></div><div class="gmail_default" style="font-size:small">--Mary</div><div class="gmail_default" style="font-size:small"><br></div></div><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Dec 1, 2015 at 1:47 PM, Daniel Barandiaran <span dir="ltr"><<a href="mailto:dbarandiaran@gmail.com" target="_blank">dbarandiaran@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div>Sorry for the bump, but I've been thinking about this a little more, and looked at some more of contributed.ncl. I think that I have a simple solution, which is just to use the ind function to pre-treat my data to ignore missing values before feeding it to the regression function.<br><br></div>If this is a poor solution, or there is a better one than feel free to chime in.<br></div><div class="HOEnZb"><div class="h5"><div class="gmail_extra"><br><div class="gmail_quote">On Tue, Dec 1, 2015 at 8:36 AM, Daniel Barandiaran <span dir="ltr"><<a href="mailto:dbarandiaran@gmail.com" target="_blank">dbarandiaran@gmail.com</a>></span> wrote:<br><blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><div dir="ltr"><div>Hi everyone,<br><br></div>In the documentation, it states that missing values are allowed, but not recommended for independent variables. However, when I give the function a time series for the dependent variable that has missing values, it says this is not allowed and dumps out. I peeked into contributed.ncl, found the function and commented out the missing value check for the dependent variable. The function seems to work properly. Is this ok?<br><br>I am using this function to reconstruct snow course SWE measurements with tree-rings. Some snow courses have a missing value or two in their record, but still have sufficient number of observations to result in reasonable regression models, and so I would still like to be able to use them.<span><font color="#888888"><br clear="all"><br><div><div>-- <br><div><div dir="ltr"><div>Danny Barandiaran<br></div><div>Ph.D. Candidate<br></div><div><div>Department of Plants, Soils, and Climate</div><div>Utah State University</div><div><br><div><br></div></div></div></div></div>
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</blockquote></div><br><br clear="all"><br>-- <br><div><div dir="ltr"><div>Danny Barandiaran<br></div><div>Ph.D. Candidate<br></div><div><div>Department of Plants, Soils, and Climate</div><div>Utah State University</div><div><br><div><br></div></div></div></div></div>
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