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Non Linear Regression: Power Curve
  Assuming that our model is power curve
   , we can take logarithm to both sides of the equation.
   , we can take logarithm to both sides of the equation.
  
 
   
 
  To compute manually, we take logarithm to both
   and
   and
    . Thus, we have model transformation
    . Thus, we have model transformation
     and
     and
      .
      .
 
Example
  Data:
   
 
   
 
  Then we plot log x versus log y and if the data is fit into a power curve, we will obtain a linear model in the double log plot. For our data we find
   with R-squared of 0.9999. Thus, the data fits into power curve. The parameters of the power curve can be obtained from the linear model using parameter transformation
   with R-squared of 0.9999. Thus, the data fits into power curve. The parameters of the power curve can be obtained from the linear model using parameter transformation
    and
    and
     . In this case, we have
     . In this case, we have
      or
      or
       . Thus, the regression line is
       . Thus, the regression line is
        with the same R-squared of 0.9999
        with the same R-squared of 0.9999
       
      
     
    
   
  
 
   
 
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   See Also
  
  :
  
   Regression tutorial
  
  ,
  
   Power Rules
  
  ,
  
   Logarithm Rules
  
  ,
  
   Kernel Regression
  
  
  
   
  
 
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