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Test parameters of Wood's model

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Test parameters of Wood's model

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Hi guys 

 

In this model how to test the params of this model if are they significant or not to fit a lactation curve by using Wood's question? and also what is the best method for this model to use? 

 

regards 

 

Ibrahim

 

proc nlin data = new   plots = fit;
  parms A = 15 B = 0.19 C = -0.0012 ;
  bounds  A B C > 0; 
    by pr  ;
  model  TEST_DAY_MILK_KG = A * Time **b * exp(-C*Time);
  output out = Fit predicted = Pred ;
 run;
QUIT;

 


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‎11-14-2017 06:54 AM
SAS Super FREQ
Posts: 4,243

Re: Test parameters of Wood's model

I don't know what "Wood's method" is, but the ParameterEstimates table includes 95% confidence intervals. If the CIs include 0, then the parameter estimates are not significantly different from 0.

 

The "best" method is the one that converges fastest for your data. For this model that has one explanatory variable, I see no reason to favor one method over another. I would use the default unless it doesn't converge. 

 

By the way, your initial guess for C violates the constraint that C > 0.

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‎11-14-2017 06:54 AM
SAS Super FREQ
Posts: 4,243

Re: Test parameters of Wood's model

I don't know what "Wood's method" is, but the ParameterEstimates table includes 95% confidence intervals. If the CIs include 0, then the parameter estimates are not significantly different from 0.

 

The "best" method is the one that converges fastest for your data. For this model that has one explanatory variable, I see no reason to favor one method over another. I would use the default unless it doesn't converge. 

 

By the way, your initial guess for C violates the constraint that C > 0.

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