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From |
"Nick Cox" <n.j.cox@durham.ac.uk> |

To |
<statalist@hsphsun2.harvard.edu> |

Subject |
st: RE: RE: RE: RE: RE: RE: re: problem using predictnl after obtaining non-linear estimates |

Date |
Sun, 26 Oct 2008 18:16:34 -0000 |

My worries on your behalf remain. If I were reviewing any paper in this field with so many parameters in a model, I would ask for a clear demonstration or argument that such complexity was essential. I've made my point, so I won't pursue it beyond this. Nick n.j.cox@durham.ac.uk -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Lopa Chakraborti Sent: 26 October 2008 17:44 To: statalist@hsphsun2.harvard.edu Subject: st: RE: RE: RE: RE: RE: re: problem using predictnl after obtaining non-linear estimates I do have data on upstream water quality which explains why the R-square is so high. ________________________________________ From: owner-statalist@hsphsun2.harvard.edu [owner-statalist@hsphsun2.harvard.edu] On Behalf Of Nick Cox [n.j.cox@durham.ac.uk] Sent: Sunday, October 26, 2008 1:41 PM To: statalist@hsphsun2.harvard.edu Subject: st: RE: RE: RE: RE: re: problem using predictnl after obtaining non-linear estimates I've never used this command. Others should have better advice on it. But if your model is not based on the flow data you would like, doesn't a R-square of 98% worry you? How can you get a model fit that appears that good without a scientifically sound model? I don't have your data and I've not studied your model, but that implies overfitting to me. Nick n.j.cox@durham.ac.uk Lopa Chakraborti The problem I am having is figuring out what goes inside the parenthesis in predict() since it is not the linear predictor xb(). Help on this would be appreciated. It is a very rough and approximate model for Streeter-Phelps. I do not have any stream flow etc data and hence I am using the monitoring station dummies to control for them. Nick Cox [n.j.cox@durham.ac.uk] No programming is needed; this is something available to you as part of your -predictnl- command. Kit is pointing you to special functions -predict()- and -xb()- that you can use within -predictnl-. I too no longer have Stata 8.2 on my machine but I do have the Stata 8 manuals, which indicate to me that these functions were present in -predictnl- in Stata 8. Therefore study the on-line help first and then the manual entry. Incidentally, I feel very queasy about an 91-parameter model, even with this kind of data (which is not alien to me). What's the engineering hydrology behind that? Lopa Chakraborti Thanks you have pointed me to the right direction. However, I am not using either predict() or xb() functions. Instead, I have: predictnl bod1 = ($K2/($K1-$K2))*exp(-$K1*aggthirdfourthadd)*(exp(-$K2*seconddistadd)-exp (-$K1*seconddistadd)). That said my limited knowledge in programming might also explain why I cannot make the connection. Kit Baum [baum@bc.edu] Lopa said I have a general question about predictnl and that is does it evaluate any function as in any NL function of the parameters and some explanatory variables or does it only predict dependent variables as is usually done. [R] predictnl -- Obtain nonlinear predictions, standard errors, etc., after estimation That help indicates that " pnl_exp is any valid Stata expression" so that you may calculate any function for each observation, not just the standard predicted value. In Stata 10 help, When calculating inference-related quantities such as standard errors, pnl_exp is evaluated repeatedly for different values of the model parameters. Therefore, think of predict() and xb() as a means of substituting for the formula of the calculation and not a means of substituting the value of the calculation that is obtained when the model parameters are set to any specific values. For example, . predict double pred_var, predict_options . predictnl newvar = pred_var, se(newvar_se) will give standard errors (newvar_se) equal to zero, since once evaluated, pred_var will contain values that are fixed with respect to e(b). Instead, . predictnl newvar = predict(predict_options), se(newvar_se) will produce what is intended. which states that zero standard errors will result. I have no idea whether it works this way in Stata 8.2. * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/

**Follow-Ups**:**st: RE: RE: RE: RE: RE: RE: RE: re: problem using predictnl after obtaining non-linear estimates***From:*Lopa Chakraborti <lchakraborti@arec.umd.edu>

**References**:**st: re: problem using predictnl after obtaining non-linear estimates***From:*Kit Baum <baum@bc.edu>

**st: RE: re: problem using predictnl after obtaining non-linear estimates***From:*Lopa Chakraborti <lchakraborti@arec.umd.edu>

**st: RE: RE: re: problem using predictnl after obtaining non-linear estimates***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**st: RE: RE: RE: re: problem using predictnl after obtaining non-linear estimates***From:*Lopa Chakraborti <lchakraborti@arec.umd.edu>

**st: RE: RE: RE: RE: re: problem using predictnl after obtaining non-linear estimates***From:*"Nick Cox" <n.j.cox@durham.ac.uk>

**st: RE: RE: RE: RE: RE: re: problem using predictnl after obtaining non-linear estimates***From:*Lopa Chakraborti <lchakraborti@arec.umd.edu>

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