Zobrazeno 1 - 10
of 310
pro vyhledávání: '"Leipus, Remigijus"'
Autor:
Jokubaitis, Saulius, Leipus, Remigijus
In this paper we study the asymptotic normality in high-dimensional linear regression. We focus on the case where the covariance matrix of the regression variables has a KMS structure, in asymptotic settings where the number of predictors, $p$, is pr
Externí odkaz:
http://arxiv.org/abs/2203.04154
We discuss joint spatial-temporal scaling limits of sums $A_{\lambda,\gamma}$ (indexed by $(x,y) \in \mathbb{R}^2_+$) of large number $O(\lambda^{\gamma})$ of independent copies of integrated input process $X = \{X(t), t \in \mathbb{R}\}$ at time sca
Externí odkaz:
http://arxiv.org/abs/2112.01893
Autor:
Leipus, Remigijus1 (AUTHOR) remigijus.leipus@mif.vu.lt, Šiaulys, Jonas2 (AUTHOR) jonas.siaulys@mif.vu.lt, Danilenko, Svetlana3 (AUTHOR) svetlana.danilenko@vilniustech.lt, Karasevičienė, Jūratė2 (AUTHOR)
Publikováno v:
Axioms (2075-1680). Jun2024, Vol. 13 Issue 6, p355. 21p.
This paper aims to examine the use of sparse methods to forecast the real, in the chain-linked volume sense, expenditure components of the US and EU GDP in the short-run sooner than the national institutions of statistics officially release the data.
Externí odkaz:
http://arxiv.org/abs/1906.07992
Autor:
Buteikis, Andrius, Leipus, Remigijus
Publikováno v:
Modern Stochastics: Theory and Applications 2019, Vol. 6, No. 2, 227-249
A bivariate integer-valued autoregressive process of order 1 (BINAR(1)) with copula-joint innovations is studied. Different parameter estimation methods are analyzed and compared via Monte Carlo simulations with emphasis on estimation of the copula d
Externí odkaz:
http://arxiv.org/abs/1906.02183
The present paper obtains a complete description of the limit distributions of sample covariances in N x n panel data when N and n jointly increase, possibly at different rate. The panel is formed by N independent samples of length n from random-coef
Externí odkaz:
http://arxiv.org/abs/1810.11204
It is well-known that random-coefficient AR(1) process can have long memory depending on the index $\beta$ of the tail distribution function of the random coefficient, if it is a regularly varying function at unity. We discuss estimation of $\beta$ f
Externí odkaz:
http://arxiv.org/abs/1710.09735
Publikováno v:
In International Journal of Forecasting April-June 2021 37(2):759-776
Publikováno v:
Journal of Multivariate Analysis 153 (2017) 121-135
We discuss nonparametric estimation of the distribution function $G(x)$ of the autoregressive coefficient $a \in (-1,1)$ from a panel of $N$ random-coefficient AR(1) data, each of length $n$, by the empirical distribution function of lag 1 sample aut
Externí odkaz:
http://arxiv.org/abs/1509.07747