State Space Modeling UsingSAS

State Space Modeling Using SAS

This article provides a brief introduction to the state space modeling capabilities in SAS, a well-known statistical software system. SAS provides state space modeling in a few different settings. SAS/ETS, the econometric and time series analysis module of the SAS system, contains many procedures that use state space models to analyze univariate and multivariate time series data. In addition, S...

Modeling Volatility Using State Space Models

In time series problems, noise can be divided into two categories: dynamic noise which drives the process, and observational noise which is added in the measurement process, but does not influence future values of the system. In this framework, we show that empirical volatilities (the squared relative returns of prices) exhibit a significant amount of observational noise. To model and predict t...

A State-space Method for Language Modeling

In this paper, a new state-space method for language modeling is presented. The complexity of the model is controlled by choosing the dimension of the state instead of the smoothing and back-off methods common in n-gram modeling. The model complexity also controls the generalization ability of the model, allowing the model to handle similar words in similar manner. We compare the state-space mo...

A Practical Guide to State Space Modeling

State-Space Architectures for Binaural Environment Modeling

Binaural displays for immersive listening must model reverberant environments, multiple sound sources, and accommodate source and head motion. Many displays model such phenomena as a collection of spatially distributed point sources; source signals are filtered with multiple head-related transfer functions (HRTFs) and then combined into a single binaural signal for display. The computational lo...