`#include <CNCL/LREF.h>' Distribution Function F(x)
`#include <CNCL/LREG.h>' Complementary Distribution Function
G(x)
TYPE
----
`CN_LREF'
`CN_LREG'
* Menu:
BASE CLASSES
------------
* CNStatistics:: Base Class of Statistic Classes
* CNLRE:: LRE Base Class
DERIVED CLASSES
---------------
RELATED CLASSES
---------------
* CNDLRE:: Discrete LRE
DESCRIPTION
-----------
The `CNLREF' and `CNLREG' classes provide the statistical evaluation
of random sequences by the LRE algorithm. Results are the distribution
(d.f.) and the complementary distribution function (c.d.f.)
respectively, the local correlation coefficient, and the error of each
discovered point. The simulation run time is controlled by a predefined
maximum error regarding to the local correlation of the input values.
For further information refer to "Effective Control of Simulation Runs
by a New Algorithm for Correlated Random Sequences" by F. Schreiber,
AEUe Vol. 42, pp. 347-354, 1988.
Constructors:
`CNLREF( CNParam * param )'
`CNLREF( double MIN=0.01, double MAX=0.99, double MAX_ERR=0.05, int LEVEL=100,'
`Scale SCALE=CNLRE::LIN, int MAXSORT= 0, char* NAME = "no named", char* TEXT ="no text";)'
`'
Initializes a `CNLREF' evaluation.
Parameters:
`MIN, MAX'
limits of d.f. and c.d.f respectively
`MAX_ERR'
maximum error of d.f. and d.f respectively
`LEVEL'
number of levels
`SCALE'
scale of ordinate (`CNLRE::LIN' or `CNLRE::LOG')
`MAXSORT'
maximum size of an internal sort array
`NAME'
allows to name the evaluation.
`TEXT'
a short explanation of the evaluation.
`CNLREG( CNParam * param )'
`CNLREG( double MIN=0.01, double MAX=0.99, double MAX_ERR=0.05, int LEVEL=100, Scale SCALE=LIN, int MAXSORT= 0, char* NAME = "no name", char* TEXT = "no text")'
Initializes a `CNLREG' evaluation. The parameters are the same as
described above.
In addition to the member functions required by CNCL and
`CNStatistics', `CNLREF' and `CNLREG' provide:
`void set_base(double b);'
Set base for conditional probablity.
`void change_error(double ne);'
Change desired error during simulation.
`long min_index() const;'
`long max_index() const;'
Return start and end of result arrary. Should be used together with
`get_result()' to acquire online evaluation during simulation.
`const CNLRE::resultline *get_result(long lev);'
Can be used to acquire online (preliminary) results of the LRE[FG]
during simulation. The parameter `lev' must be in the range
`min_index' to `max_index'. A result line is a structs with the
members `x', `vf' -- holds F- or G-value --, `rho', `sigrho', `d'
-- the relative error -- and `nx' -- the number of exact hits of
`x'.
`double cur_x_lev() const;'
Returns the x-level currently calculated.
`double cur_f_lev();'
`double cur_g_lev();'
These return the current F- resp. G-level in calculation.
