scholarly journals On the Discrepancy of Random Walks on the Circle

2019 ◽  
Vol 14 (2) ◽  
pp. 73-86
Author(s):  
Alina Bazarova ◽  
István Berkes ◽  
Marko Raseta

AbstractLet X1,X2,... be i.i.d. absolutely continuous random variables, let {S_k} = \sum\nolimits_{j = 1}^k {{X_j}} (mod 1) and let D*N denote the star discrepancy of the sequence (Sk)1≤k≤N. We determine the limit distribution of \sqrt N D_N^* and the weak limit of the sequence \sqrt N \left( {{F_N}(t) - t} \right) in the Skorohod space D[0, 1], where FN (t) denotes the empirical distribution function of the sequence (Sk)1≤k≤N.

1967 ◽  
Vol 10 (5) ◽  
pp. 739-741
Author(s):  
Miklós Csörgo

Let X1 …, Xn be mutually independent random variables with a common continuous distribution function F (t). Let Fn(t) be the corresponding empirical distribution function, that isFn(t) = (number of Xi ≤ t, 1 ≤ i ≤ n)/n.Using a theorem of Manija [4], we proved among others the following statement in [1].


1971 ◽  
Vol 8 (2) ◽  
pp. 321-330 ◽  
Author(s):  
Lajos Takács

Let ξ1, ξ2, ···, ξm be mutually independent random variables having a common distribution function P{ξr≦x} = F(x)(r = 1, 2, ···, m). Let Fm(x) be the empirical distribution function of the sample (ξ1, ξ2, ···, ξm), that is, Fm(x) is defined as the number of variables ≦x divided by m.


1971 ◽  
Vol 8 (02) ◽  
pp. 321-330 ◽  
Author(s):  
Lajos Takács

Let ξ 1 , ξ2, ···, ξm be mutually independent random variables having a common distribution function P {ξ r ≦x} = F(x)(r = 1, 2, ···, m). Let Fm (x) be the empirical distribution function of the sample (ξ 1, ξ 2 , ···, ξm), that is, Fm (x) is defined as the number of variables ≦x divided by m.


1965 ◽  
Vol 8 (1) ◽  
pp. 93-103 ◽  
Author(s):  
Miklós Csörgo

Let F(x) be the continuous distribution function of a random variable X and Fn(x) be the empirical distribution function determined by a random sample X1, …, Xn taken on X. Using the method of Birnbaum and Tingey [1] we are going to derive the exact distributions of the random variablesand and where the indicated sup' s are taken over all x' s such that -∞ < x < xb and xa ≤ x < + ∞ with F(xb) = b, F(xa) = a in the first two cases and over all x' s so that Fn(x) ≤ b and a ≤ Fn(x) in the last two cases.


1967 ◽  
Vol 19 ◽  
pp. 550-558 ◽  
Author(s):  
Miklós Csörgö

Let X1 X2, … , Xn be mutually independent random variables with a common continuous distribution function F(t). Let Fn(t) be the corresponding empirical distribution function, that is Fn(t) = (number of Xi ⩽ t, 1 ⩽ i ⩽ n)/n.


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