R - Adjusting squared root function with lm -


I want to adjust a function like this: 

  fit4 = lm (mut ~ Ent + Score + Vatt + I (Ent ^ 2) + I (Score ^ 2) + I (wt ^ 2))   
 When I  summary (Fit 4) < / Code> I see:  
  coefficient: estimate estimate error t value P (> | t |) (interception) -1.779381 0.086256 -20.629   
 I would like to receive it now but the original class of the above work is doing the error: sqrt (ent + score + wt + i (ent ^ 2) + I (score ^ 2) + I (wt ^ 2)), but when I just add "sqrt ()", then summarizes something:  
  Estimates (interruption) 1.066025 (Sqrt (ent + score + weight) + I (ent ^ 2) + I (score ^ 2) + I (wt ^ 2)) -0.24028   
 (For more studs Error, T-value, etc.)  
 How do I add "root squared" or "log" and for each element of the function the mother I can get?   
 
 
 You must apply the function to all those that induvidually  
 < Code> fit4 = lm (mut ~ log ++ log (score) + log (wt) + log (INT ^ 2) + log (I (score ^ 2)) + log (I (wt ^ 2 )   
 will be  
 due:  
  log (ent + score + plus + i (ent ^ 2) + I (score ^ 2) + I (wt ^ 2))   
 is interpreted as a single regressor, then for R, it is  lm (mut ~ x) < / Code> is like  x = log (...) instead of   
  x = is like log (ant) + ... + log (I ( Wt ^ 2))

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