5 research outputs found
Testing of random matrices
Let be a positive integer and be an
\linebreak \noindent sized matrix of independent random variables
having joint uniform distribution \hbox{Pr} {x_{ij} = k \hbox{for} 1 \leq k
\leq n} = \frac{1}{n} \quad (1 \leq i, j \leq n) \koz. A realization
of is called \textit{good}, if its each row and
each column contains a permutation of the numbers . We present and
analyse four typical algorithms which decide whether a given realization is
good
Quick Testing of Random Sequences
Abstract Let ξ be a random integer sequence, having uniform distribution A realization (i1, i2, . . . , in) of ξ is called good, if its elements are different. We present seven algorithms which decide whether a given realization is good. The investigated problem is connected with design of experiment
Testing of sequences by simulation
Let be a random integer vector, having uniform distribution
A realization of is called
\textit{good}, if its elements are different. We present algorithms
\textsc{Linear}, \textsc{Backward}, \textsc{Forward}, \textsc{Tree},
\textsc{Garbage}, \textsc{Bucket} which decide whether a given realization is
good. We analyse the number of comparisons and running time of these algorithms
using simulation gathering data on all possible inputs for small values of
and generating random inputs for large values of