JKQTPlotter an extensive Qt4/Qt5 Plotter framework (including a fast variant and a LaTeX equation renderer!), written fully in C/C++ and without external dependencies
Statistical Computations
Collaboration diagram for Statistical Computations: ## Modules

1-dimensional Histograms

1-dimensional Kernel Density Estimates

2-dimensional Histograms

2-dimensional Kernel Density Estimates

Basic statistics

Grouped statistics

Polynomial Fits/Regression

Regression Analysis

## Detailed Description

This group contains a statistics library, which offers several basic methods and is based on an iterator interface:

In addition there is a set of "adaptors" (see Statistics To Plot Adaptors ) that shortcut the calculation of a statistical property and the subsequent parametrization of a plot with the results. With these adaptors you can add e.g. a boxplot or histogram chart to a plot by calling only one function.

All statistics functions use an iterator-based interface, comparable to the interface of the algorithms in the C++ standard template library. To this end, the class `JKQTPDatastore` provides an iterator interface to its columns, using the functions `JKQTPDatastore::begin()` and `JKQTPDatastore::end()`. Both functions simply receive the column ID as parameter and exist in a const and a mutable variant. the latter allows to also edit the data. In addition the function `JKQTPDatastore::backInserter()` returns a back-inserter iterator (like generated for STL containers with `std::back_inserter(container)`) that also allows to append to the column.

Note that the iterator interface allows to use these functions with any container that provides such iterators (e.g. `std::vector<double>`, `std::list<int>`, `std::set<float>`, `QVector<double>`...).

Code using one of these statistics functions therefore may look e.g. like this:

// mean of a column in a JKQTPDatastore:
double mean=jkqtpstatAverage(datastore1->begin(randomdatacol1), datastore1->end(randomdatacol1));
// mean of a std::vector
std::vector<double> data {1,2,4,5,7,8,10,2,1,3,5};
double meanvec=jkqtpstatAverage(data.begin(), data.end());

All statistics functions use all values in the given range and convert each value to a `double`, using `jkqtp_todouble()`. The return values is always a dohble. Therefore you can use these functions to calculate statistics of ranges of any type that can be converted to `double`. Values that do not result in a valid `double`are not used in calculating the statistics. Therefore you can exclude values by setting them `JKQTP_DOUBLE_NAN` (i.e. "not a number").