Dear all,
Considering the different growth curves that are applied in biology as well as in economics, which factors distinguish their assumptions? For example, exponential, logistic, monomolecular, and Gompertz curves are common in biology - either in assessing pathological fields or in entomology trials. Curves like linear, quadratic, and other curves are common in economic growth analysis.
Having an annual discrete time series data of foodgrain production for about 30-40 years, would it be reasonable to choose either a logistic or a Gompertz model (given that the scatter of data series resemble few of the above)? In which aspects do the assumptions among these models compete with each other?
Lorenz Curve
The Lorenz curve is used in economics and ecology to describe inequality in wealth or size. The Lorenz curve is a function of the cumulative proportion of ordered individuals mapped onto the corresponding cumulative proportion of their size. Given a sample of n ordered individuals with x_i^' the size of individual i and x_1^'
Very interesting question Balaji. I have spent many hard days working on these and finally came to a simple conclusion. Plot the data against time. Based on the possible trends fit a few models and choose the best fit based on Adj. R Sq. If you find a better solution practically, gimme a mail or call :)
I believe that first you shal specify the variable that grows, as not all of them perfome the same time-dependend behaviour.
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