CumFreq:   Cumulative frequency analysis with probability distribution fitting
Free download of software

Summary: The CumFreq model program calculates the cumulative (no exceedance, non-exceedance) frequency and it does probability distribution fitting of data series, e.g. crop production, soil properties, salinity, depth to watertable (water-table), rainfall, river and drain discharge, groundwater (ground-water) and river level, hydraulic conductivity and soil permeability for water.
      The computer program fits various linear, logarithmic, exponential and double exponential cumulative frequency distributions, including the normal, log-normal (lognormal), (log)logistic, Cauchy, Pareto, Weibull, Frechet (Fisher-Tippett type II), and Gumbel probability distributions, and selects the best fitting distribution using the method of best fit.
Some of the distributions are useful for extreme value analysis.
      Preference for a specific distribution can also be expressed.
The Cumfreq calculator model not only uses logarithmic but also exponential transformations of the data. The exponent (greater than 0) is optimized automatically. These so called generalized distributions have great flexibility, but they are mostly not used in other distribution fitting software.
      Further, the Cumfreq application (app) uses mirrored distributions that reverse the skewness, so that the number of distributions that are possibly applicable is enlarged.
The Cumfreq program calculator allows negative data. In case of distributions that do not support negative data, the distribution is shifted in positive direction so that they are made applicable.
      The download and use of the CumFreq model program is totally free. It is freeware.

Details: When the mathematical model program detects a discontnuous probability function, it gives the user the choice to introduce a breakpoint (break-point) or threshold value, yielding a segmented or composite frequency and probability distribution.
      The resulting probability distribution is accompanied by 90% confidence limits and belts (bands) and return periods (recurrence intervals).
The program also divides the range of data into a number of equal intervals and calculates an interval frequency distribution or histogram. The number of intervals is to be given by the user.
      On 22 March 2018 the option to see a list of distributions ranked according to their goodness of fit was introduced.
On 6 April 2018, next to the cumulative distribution function (CDF), the probability density function (PDF) was inlcluded in the histogram graph.
      Examples are given.

Start: The program starts clicking on CumFreq.Exe. More details are given in the program itself.

Documentation: A lecture note ("Data Analysis") on statistical analysis with examples of CumFreq applications is found on the articles page. Further, this page gives an article binomial confidence limits for cumulative probability distributions.
          The principles of frequency analysis can be found in a lecture note on the FAQ's page. Further, this page gives a summary paper on binomial confidence limits for cumulative frequency distributions.

Experiences: For improvement, I am interested to learn about your experiences with CumFreq. For this there is a contact form.

Acknowlegment: Thanks to a suggestion by Madhu Kandampadath the generalized extreme value (GEV) distribution was included in the list of options on 17 February 2018. Two days later the composite Laplace distribution was added.

Hint: An amplified version of CumFreq named CumFreqA can be seen on: composite distributions. This version contains extra facilities regarding composite probability distributions.

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CumFreq


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introduction to cumfreq Introduction screen to CumFreq program (model).
The CumFreq calculator models the cumulative (non-exceedance) 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 cumulative frequency 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, as well as a cut-off (threshold) velue.
example distribution
           fitting 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 and
       frequency 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.

list of probability
       distributions ranked by goodness of fit Probability distributions ranked by goodness of fit
CumFreq provides the option to produce a list of probability distributions ranked by goodness of fit.

Calculator for
       probability values 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.

composite probability
       distributions Composite probabilty distributions.
The amplified CumFreq software (CumFreqA) provides the possibility to select a composite probability distribution (like the Laplace distribution) or to find the best fitting of all.

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