What if I know that my uncertain parameter C from a model equation C*exp(T/T0) is in a certain range… but then I wonder whether I should instead be evaluating the exact same equation as exp(T/T0 + D) (with D = ln(C), C = exp(D))? Do I use the uniform distribution on C, which will correspond to a skewed distribution on D, or do I use the uniform distribution on D which will correspond to a skewed distribution on C?
Well if it’s you know it’s in [0,1], then you’ve got a perfectly good uniform distribution.
What if I know that my uncertain parameter C from a model equation C*exp(T/T0) is in a certain range… but then I wonder whether I should instead be evaluating the exact same equation as exp(T/T0 + D) (with D = ln(C), C = exp(D))? Do I use the uniform distribution on C, which will correspond to a skewed distribution on D, or do I use the uniform distribution on D which will correspond to a skewed distribution on C?