6 citations · 10 across the 8 of their papers we have counts for
9 papers
Generalized Autoregressive Multivariate Models: From Binary to Poisson
Anna Bykhovskaya, Nour Meddahi
This paper presents a framework for binary autoregressive time series in which each observation is a Bernoulli variable whose success probability evolves with past outcomes and pro…
Estimation of a Dynamic Tobit Model with a Unit Root
Anna Bykhovskaya, James A. Duffy
This paper studies robust estimation in the dynamic Tobit model under local-to-unity (LUR) asymptotics. We show that both Gaussian maximum likelihood (ML) and censored least absolu…
Largevars: An R Package for Testing Large VARs for the Presence of Cointegration
Anna Bykhovskaya, Vadim Gorin, Eszter Kiss
Cointegration is a property of multivariate time series that determines whether its non-stationary, growing components have a stationary linear combination. Largevars R package con…
How weak are weak factors? Uniform inference for signal strength in signal plus noise models
Anna Bykhovskaya, Vadim Gorin, Sasha Sodin
The paper analyzes four classical signal-plus-noise models: the factor model, spiked sample covariance matrices, the sum of a Wigner matrix and a low-rank perturbation, and canonic…
Canonical Correlation Analysis: review
Anna Bykhovskaya, Vadim Gorin
For over a century canonical correlations, variables, and related concepts have been studied across various fields, with contributions dating back to Jordan [1875] and Hotelling [1…
High-Dimensional Canonical Correlation Analysis
Anna Bykhovskaya, Vadim Gorin
This paper studies high-dimensional canonical correlation analysis (CCA) with an emphasis on the vectors that define canonical variables. The paper shows that when two dimensions o…
The Local to Unity Dynamic Tobit Model
Anna Bykhovskaya, James A. Duffy
This paper considers highly persistent time series that are subject to nonlinearities in the form of censoring or an occasionally binding constraint, such as are regularly encounte…
Asymptotics of Cointegration Tests for High-Dimensional VAR()
Anna Bykhovskaya, Vadim Gorin
The paper studies nonstationary high-dimensional vector autoregressions of order , VAR(). Additional deterministic terms such as trend or seasonality are allowed. The number…
Cointegration in large VARs
Anna Bykhovskaya, Vadim Gorin
The paper analyses cointegration in vector autoregressive processes (VARs) for the cases when both the number of coordinates, , and the number of time periods, , are large an…