Sliced average variance estimation for multivariate time series

Asymptotics for sliced average variance estimation

In this paper, we systematically study the consistency of sliced average variance estimation (SAVE). The findings reveal that when the response is continuous, the asymptotic behavior of SAVE is rather different from that of sliced inverse regression (SIR). SIR can achieve √ n consistency even when each slice contains only two data points. However, SAVE cannot be √ n consistent and it even turns...

A note on extension of sliced average variance estimation to multivariate regression

Rand Corporation, Pittsburgh, PA 15213 e-mail: [email protected] Abstract: Many sufficient dimension reduction methodologies for univariate regression have been extended to multivariate regression. Sliced average variance estimation (SAVE) has the potential to recover more reductive information, and recent development enables us to test the dimension and predictor effects with distributions comm...

Estimation of Time - Average Variance Constants

For statistical inference of means of stationary processes, one needs to estimate their time-average variance constants (TAVC) or long-run variances. For a stationary process, its TAVC is the sum of all its covariances and it is a multiple of the spectral density at zero. The classical TAVC estimate which is based on batched means does not allow recursive updates and the required memory complex...

Recursive Estimation of Time - Average Variance Constants

For statistical inference of means of stationary processes, one needs to estimate their time-average variance constants (TAVC) or long-run variances. For a stationary process, its TAVC is the sum of all its covariances and it is a multiple of the spectral density at zero. The classical TAVC estimate which is based on batched means does not allow recursive updates and the required memory complex...

Variance Estimation in Time Series Regression Models