scholarly journals Ewens Sampling and Invariable Generation

2018 ◽  
Vol 27 (6) ◽  
pp. 853-891 ◽  
Author(s):  
GERANDY BRITO ◽  
CHRISTOPHER FOWLER ◽  
MATTHEW JUNGE ◽  
AVI LEVY
Keyword(s):  
Symmetric Group ◽  
Fixed Number ◽  
Probability Measures ◽  
Random Permutations ◽  
Positive Probability ◽  
Ewens Sampling Formula ◽  
Sampling Formula ◽  
Special Case ◽  
The Way

We study the number of random permutations needed to invariably generate the symmetric group Sn when the distribution of cycle counts has the strong α-logarithmic property. The canonical example is the Ewens sampling formula, for which the special case α = 1 corresponds to uniformly random permutations.For strong α-logarithmic measures and almost every α, we show that precisely ⌈(1−αlog2)−1⌉ permutations are needed to invariably generate Sn with asymptotically positive probability. A corollary is that for many other probability measures on Sn no fixed number of permutations will invariably generate Sn with positive probability. Along the way we generalize classic theorems of Erdős, Tehran, Pyber, Łuczak and Bovey to permutations obtained from the Ewens sampling formula.

Generation of the symmetric group Sn2

2021 ◽  
pp. 2150107
Author(s):  
Carlos Zequeira Sánchez ◽  
Evaristo José Madarro Capó ◽  
Guillermo Sosa-Gómez
Keyword(s):  
Symmetric Group ◽  
Random Element ◽  
Matrix Representation ◽  
Random Permutation ◽  
Random Permutations ◽  
Dimension Formula ◽  
Indispensable Tool

In various scenarios today, the generation of random permutations has become an indispensable tool. Since random permutation of dimension [Formula: see text] is a random element of the symmetric group [Formula: see text], it is necessary to have algorithms capable of generating any permutation. This work demonstrates that it is possible to generate the symmetric group [Formula: see text] by shifting the components of a particular matrix representation of each permutation.

Double Value-Ranges

2019 ◽  
pp. 167-181
Author(s):  
Peter Simons
Keyword(s):  
Combinatory Logic ◽  
Special Case ◽  
The Way

From the time of Begriffsschrift onwards, Frege treated functions of two or more places on a par with those of one place. This included the treatment of relations (Beziehungen) as a special case of polyadic functions in the way that concepts (Begriffe) were a special case of monadic functions. By the time of Grundgesetze (and unlike in Begriffsschrift), Frege dealt with relations largely through their extensions, which were what he called “double value-ranges” (Doppelwerthverläufe). This is in some ways a misnomer, since double value-ranges are simply a special case of single or ordinary value-ranges, namely value-ranges of functions derived from the value-ranges of monadic functions with additional saturated places. Frege’s treatment of the extensions of relations (which he came to call simply “Relationen”) thus embodies a move analogous to the treatment of polyadic functions as functions of functions, a device invented in 1920 by Moses Schönfinkel and since (unfairly) known in combinatory logic as “currying”. This paper considers the details of Frege’s Grundgesetze treatment of relations via their extensions, exhibits its grammar, and indicates its formal elegance by comparing it with other possible treatments.

Minimal Complete Class of Linear Unbiased Estimators of Population Mean for a Special Sampling Design1

1989 ◽  
Vol 38 (1-2) ◽  
pp. 71-82
Author(s):  
J. A. Patel ◽  
H. C. Patel
Keyword(s):  
Finite Population ◽  
Positive Probability ◽  
Complete Class ◽  
Population Mean ◽  
Unbiased Estimators ◽  
Homogeneous Linear ◽  
Special Case

In this paper we give a complete description of the minimal complete subclass of C the class of all homogeneous linear unbiased estimators of a finite population mean for the extremely special case of taking sample of size 2 units from a population of size 4, where only samples containing units ( U1, Ui+ 1) have equal positive probability.

scholarly journals On the Outlying Eigenvalues of a Polynomial in Large Independent Random Matrices

2019 ◽  
Author(s):  
Serban T Belinschi ◽  
Hari Bercovici ◽  
Mireille Capitaine
Keyword(s):  
Probability Theory ◽  
Random Matrices ◽  
Empirical Distribution ◽  
Free Probability ◽  
Probability Measures ◽  
Unitary Operators ◽  
Free Probability Theory ◽  
Wigner Matrix ◽  
Asymptotic Eigenvalue ◽  
Special Case

Abstract Given a selfadjoint polynomial $P(X,Y)$ in two noncommuting selfadjoint indeterminates, we investigate the asymptotic eigenvalue behavior of the random matrix $P(A_N,B_N)$, where $A_N$ and $B_N$ are independent Hermitian random matrices and the distribution of $B_N$ is invariant under conjugation by unitary operators. We assume that the empirical eigenvalue distributions of $A_N$ and $B_N$ converge almost surely to deterministic probability measures $\mu$ and $\nu$, respectively. In addition, the eigenvalues of $A_N$ and $B_N$ are assumed to converge uniformly almost surely to the support of $\mu$ and $\nu ,$ respectively, except for a fixed finite number of fixed eigenvalues (spikes) of $A_N$. It is known that almost surely the empirical distribution of the eigenvalues of $P(A_N,B_N)$ converges to a certain deterministic probability measure $\eta \ (\textrm{sometimes denoted}\ P^\square(\mu,\nu))$ and, when there are no spikes, the eigenvalues of $P(A_N,B_N)$ converge uniformly almost surely to the support of $\eta$. When spikes are present, we show that the eigenvalues of $P(A_N,B_N)$ still converge uniformly to the support of $\eta$, with the possible exception of certain isolated outliers whose location can be determined in terms of $\mu ,\nu ,P$, and the spikes of $A_N$. We establish a similar result when $B_N$ is replaced by a Wigner matrix. The relation between outliers and spikes is described using the operator-valued subordination functions of free probability theory. These results extend known facts from the special case in which $P(X,Y)=X+Y$.

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