This research focuses to develop some new techniques on statistical learning including methodology, computation and application. We also developed statistical quantification in nanomaterials. For a large number of random variables with temporal or spatial structures, we proposed shrink estimates...

This paper presents a new random weighting estimation method for dynamic navigation positioning. This method adopts the concept of random weighting estimation to estimate the covariance matrices of system state noises and observation noises for controlling the disturbances of singular...

Three main issues are explored in this thesis—volatility measurement, volatility spillover and large-dimension covariance matrices. For the first question of volatility measurement, this thesis compares two newly-proposed, high-frequency volatility measurement models, namely realized...

In this paper, the multipath time delay estimation (TDE) problem for a slow frequency hopping (SFH) system using rank revealing QR factorization method (RRQR) is considered. It gives precious information about numerical rank and null space. By applying the RRQR in association with the well-known...

The recently witnessed financial turmoil and the current international stability context have demonstrated the need for a deeper understandingabout ex-ante international asset price fluctuations. Moreover, it is now more evident that very little is known about real estate securities and their...

The time horizon of decision-making is an essential dimension of economic problemsbut is difficult to explicitly define. In this thesis, we use time series analysisaugmented by wavelet transform methods to precisely identify distinct time horizonsin economic data and measure their explanatory...

We provide a general framework for integration of high-frequency intraday data into the measurement, modeling, and forecasting of daily and lower frequency return volatilities and return distributions. Mostprocedures for modeling and forecasting financial asset return volatilities, correlations,...

Recent empirical studies have argued that the temporal dependencies in "nancialmarket volatility are best characterized by long memory, or fractionally integrated, timeseries models. Meanwhile, little is known about the properties of the semiparametric inference procedures underlying much of...