Re: Regression with missing values

*To*: mathgroup at smc.vnet.net*Subject*: [mg51707] Re: Regression with missing values*From*: ludenscheid1 at hotmail.com (Nikolas Kiefer)*Date*: Fri, 29 Oct 2004 03:40:47 -0400 (EDT)*References*: <clpr5j$a38$1@smc.vnet.net>*Sender*: owner-wri-mathgroup at wolfram.com

Actually, I didn't want to delete those entries. To be a little bit more explicit about my data, I have circa 5 independent variables which place the 6th dependent variable (the analysis result) into a category. Unfortunately, sometimes there exist data for which 1 of the 5 independent variables cannot be determined, and thus the data really can't be placed into a category. It's at this point that I was hoping it would be possible to still make use of the 6th data variable (which depends on the first 5 vars) by somehow "estimating" the category to which it should belong to. I know that certain statistical packages deal with such circumstances without simply deleting the data, but can Mathematica? Nik Bill Rowe <readnewsciv at earthlink.net> wrote in message news:<clpr5j$a38$1 at smc.vnet.net>... > On 10/27/04 at 1:54 AM, ludenscheid1 at hotmail.com (Nikolas Kiefer) > wrote: > > >Can Mathematica handle regression where the dependent variables > >sometimes have missing values? If so, how are these missing values > >to be represented in the data? > > How do you want the missing values treated? Simply ignored? If so, code the missing values in any manner you find suitable to easily distinguish them from valid values and use DeleteCases to delete them from the data matrix given to the regression routine you want to use. > > For example, I have a data file with optical power measurements made in dBm. Valid measurements are negative numbers. So, I used 9999 to replace the missing values. Then I use DeleteCases[data,{_,9999}] to strip these values from the data matrix.