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The standard logistic function is the logistic function with parameters =, =, =, which yields = + = + = / / + /.In practice, due to the nature of the exponential function, it is often sufficient to compute the standard logistic function for over a small range of real numbers, such as a range contained in [−6, +6], as it quickly converges very close to its saturation values of 0 and 1.
The graphs also show the approximate rate of article increase per day, along with the projected number of articles based on annual doubling referenced to January 1, 2003. The growth in articles had been approximately 100% per year from 2003 through most of 2006, but has tailed off since roughly September 2006.
The Hubbert linearization is a way to plot production data to estimate two important parameters of a Hubbert curve, the approximated production rate of a nonrenewable resource following a logistic distribution: the logistic growth rate and; the quantity of the resource that will be ultimately recovered.
In statistics, the logistic model (or logit model) is a statistical model that models the log-odds of an event as a linear combination of one or more independent variables. In regression analysis, logistic regression [1] (or logit regression) estimates the
The Hubbert curve is an approximation of the production rate of a resource over time. It is a symmetric logistic distribution curve, [ 1 ] often confused with the "normal" gaussian function . It first appeared in "Nuclear Energy and the Fossil Fuels," geologist M. King Hubbert 's 1956 presentation to the American Petroleum Institute , as an ...
To use the matrix, analysts plot a scatter graph to rank the business units (or products) on the basis of their relative market shares and growth rates. This results is a chart showing: Cash cows, where a company has high market share in a slow-growing industry. These units typically generate cash in excess of the amount of cash needed to ...
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