so, ln(m) = Gt semi-log is linear.
Weibull m = A t^(B)
so, ln(m) = lnA + B ln(t) log-log is linear.
Because Weibull takes an extra log-transformation, it 'suppresses' nosies in the data, therefore naturally fits bettern than Gomeprtz model.
Saturday, July 12, 2014
Gompertz versus Weibull, semilog versus log-log plot
Gompertz m = R exp(Gt)
so, ln(m) = Gt semi-log is linear.
Weibull m = A t^(B)
so, ln(m) = lnA + B ln(t) log-log is linear.
Because Weibull takes an extra log-transformation, it 'suppresses' nosies in the data, therefore naturally fits bettern than Gomeprtz model.
so, ln(m) = Gt semi-log is linear.
Weibull m = A t^(B)
so, ln(m) = lnA + B ln(t) log-log is linear.
Because Weibull takes an extra log-transformation, it 'suppresses' nosies in the data, therefore naturally fits bettern than Gomeprtz model.
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