
Download: CumFreq Software & models General articles & manuals Artículos (in Spanish, en Español) Published reports & cases Particular reports & cases FAQ's & answers Update record Home page 
Introduction screen to CumFreq program (model).
The CumFreq calculator models the cumulative (nonexceedance) frequency distribution and fits it to a probability distribution. It uses, amongst other, the normal, logistic, exponential and Gumbel distributions. For distribution fitting, the CumFreq software app linearizes the probability distribution.For a list of linearizations, based on logarithmic and other transformations, see: transformations 
Input tabsheet
The input tabsheet shows the probability distributions that are being used in the CumFreq software model to fit the data to. In this application program one can select "best of all" or indicate a preference. The number of intervals needed to prepare the histogram can be entered. 
Cumulative distribution fitting
Probability distribution fitting is based on plotting positions (the observed data). A 90% confidence interval of the fitted probability distribution is shown. It is a specialty of the CumFreq software model calculator to apply "generalized" distributions, which, in this application program, makes them fit better than the standard ones. They are based on an exponential transformation of the data to obtain a closer fit. The curve shown is also called cumulative distribution function (PDF). 
Histogram of fitted distribution + density function
The histogram provides the observed and calculated frequencies by interval. The histogram gives an impression of the symmetry of the probability distribution and whether it is skew to the left or to the right. The probability density function (PDF) is shown as the product of density and lenhth of the intervals. 
Probability distributions ranked by goodness of fit
CumFreq provides the option to produce a list of probability distributions ranked by goodness of fit. 
Calculator
CumFreq provides the option to calculate probabilities of data values and vice versa. The same holds for return periods. In addition confidence intervals are given. 