4 citations · 6 across the 10 of their papers we have counts for
10 papers
Tests for Independence of High-Dimensional Nonstationary Time Series
Yunyi Zhang
This manuscript studies the problem of independence testing between two high-dimensional time series without assuming weak stationarity, that is, allowing their autocovariances to…
ProbRes: Volatility Learning for Probabilistic Time-Series Forecasting
Tingting Wang, Yunyi Zhang, Benyou Wang
Probabilistic time series forecasting has attracted increasing attention in financial applications due to the need to quantify risk and uncertainty in future observations. We propo…
Statistical inference of high-dimensional vector autoregressive time series with non-i.i.d. innovations
Yunyi Zhang
Independent or i.i.d. innovations is an essential assumption in the literature for analyzing a vector time series. However, this assumption is either too restrictive for a real-lif…
Debiased and threshold ridge regression for linear model with heteroskedastic and dependent error
Yunyi Zhang, Dimitris N. Politis
Focusing on a high dimensional linear model with dependent, non-stationary, and heteroskedastic errors, this paper applies the debiased and threshold ridge regression m…
Simultaneous Statistical Inference for Second Order Parameters of Time Series under Weak Conditions
Yunyi Zhang, Efstathios Paparoditis, Dimitris N. Politis
Strict stationarity is a common assumption used in the time series literature in order to derive asymptotic distributional results for second-order statistics, like sample autocova…
Ridge Regression Revisited: Debiasing, Thresholding and Bootstrap
Yunyi Zhang, Dimitris N. Politis
The success of the Lasso in the era of high-dimensional data can be attributed to its conducting an implicit model selection, i.e., zeroing out regression coefficients that are not…
Bootstrap prediction intervals with asymptotic conditional validity and unconditional guarantees
Yunyi Zhang, Dimitris N. Politis
It can be argued that optimal prediction should take into account all available data. Therefore, to evaluate a prediction interval's performance one should employ conditional cover…
Semi-parametric estimation and prediction intervals in state space models
Yunyi Zhang, Tingting Wang, Dimitris N. Politis
Literatures in state space models focus on parametric inference and prediction, which fail if the state space model is not fully specified and the maximum likelihood estimation doe…
and almost sure convergence of estimation on heavy tail index under random censoring
Yunyi Zhang, Jiazheng Liu, Zexin Pan +1
In this paper, we prove and almost sure convergence of tail index estimator mentioned in \cite{grama2008} under random censoring and several assumptions. th mome…
Monotone function estimator and its application
Yunyi Zhang, Dimitris N. Politis, Jiazheng Liu +1
In this paper, the model with being random variables with known distribution and being unknown strictly increasing function is proposed and…