7 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…
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…
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…
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…
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…
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…