I did a regression and found that my residuals pointed out that my data is heteroscedastic. I applied the Box-Cox transformation and my new model looks as follows,
y^(1/5) = b0 + b1x1 + b2x2
with my lambda = 1/5 and I found my b0, b1 and b2 values. This transformed model does not seem to have heteroscedasticity but now I want to use these coefficients to forecast data on a hold out set I have and test the accuracy. But is it correct if i use the coefficients from the transformed model and the resulting value I must get the power of 5 in order to get the actual value forecasted that I want to compare with the actual?