AbstractLet (Ut,Vt) be a bivariate Lévy process, where Vt is a subordinator and Ut is a Lévy process formed by randomly weighting each jump of Vt by an independent random variable Xt having cdf F. We investigate the asymptotic distribution of the self-normalized Lévy process Ut/Vt at 0 and at ∞. We show that all subsequential limits of this ratio at 0 (∞) are continuous for any nondegenerate F with finite expectation if and only if Vt belongs to the centered Feller class at 0 (∞). We also characterize when Ut/Vt has a non-degenerate limit distribution at 0 and ∞
Let X=(Xt)t>=0 be a Lévy process with absolutely continuous Lévy measure [nu]. Small-time expansions...
Necessary and sufficient conditions for weak and strong convergence are derived for the weighted ver...
We obtain limit theorems for sup [alpha]n(t,s)/(t[lambda]s[mu]G(t)L(s)), where [alpha]n is the bivar...
AbstractLet (Ut,Vt) be a bivariate Lévy process, where Vt is a subordinator and Ut is a Lévy process...
We establish asymptotic distribution results for self-normalized Lévy processes at small and large t...
We prove a self normalized central limit theorem for a new mixing class of processes introduced in K...
We define a stochastic process fX n ; n = 0; 1; 2; : : :g in terms of cumulative sums of the sequenc...
Let be a linear process, where and [var epsilon]t, t[set membership, variant]Z, are i.i.d. r.v.'s in...
This book deals with topics in the area of Lévy processes and infinitely divisible distributions suc...
Consider a Levy process Xt with quadratic variation process Vt = σ2t+Σ0 0, where ΔXt = Xt -Xt- denot...
We give conditions under which the self-normalized productof independent and identically distributed...
AbstractBased on an R2-valued random sample {(yi,xi),1≤i≤n} on the simple linear regression model yi...
Let X(t) = Sigma(j)(infinity) = (-infinity) psi(j)Z(t-j) be a discrete moving average process based ...
Let X(t) = Sigma(j)(infinity) = (-infinity) psi(j)Z(t-j) be a discrete moving average process based ...
The joint distribution of X and N, where N has a geometric distribution and X is the sum of N IID ex...
Let X=(Xt)t>=0 be a Lévy process with absolutely continuous Lévy measure [nu]. Small-time expansions...
Necessary and sufficient conditions for weak and strong convergence are derived for the weighted ver...
We obtain limit theorems for sup [alpha]n(t,s)/(t[lambda]s[mu]G(t)L(s)), where [alpha]n is the bivar...
AbstractLet (Ut,Vt) be a bivariate Lévy process, where Vt is a subordinator and Ut is a Lévy process...
We establish asymptotic distribution results for self-normalized Lévy processes at small and large t...
We prove a self normalized central limit theorem for a new mixing class of processes introduced in K...
We define a stochastic process fX n ; n = 0; 1; 2; : : :g in terms of cumulative sums of the sequenc...
Let be a linear process, where and [var epsilon]t, t[set membership, variant]Z, are i.i.d. r.v.'s in...
This book deals with topics in the area of Lévy processes and infinitely divisible distributions suc...
Consider a Levy process Xt with quadratic variation process Vt = σ2t+Σ0 0, where ΔXt = Xt -Xt- denot...
We give conditions under which the self-normalized productof independent and identically distributed...
AbstractBased on an R2-valued random sample {(yi,xi),1≤i≤n} on the simple linear regression model yi...
Let X(t) = Sigma(j)(infinity) = (-infinity) psi(j)Z(t-j) be a discrete moving average process based ...
Let X(t) = Sigma(j)(infinity) = (-infinity) psi(j)Z(t-j) be a discrete moving average process based ...
The joint distribution of X and N, where N has a geometric distribution and X is the sum of N IID ex...
Let X=(Xt)t>=0 be a Lévy process with absolutely continuous Lévy measure [nu]. Small-time expansions...
Necessary and sufficient conditions for weak and strong convergence are derived for the weighted ver...
We obtain limit theorems for sup [alpha]n(t,s)/(t[lambda]s[mu]G(t)L(s)), where [alpha]n is the bivar...