Local modal regression for the spatio-temporal model

Local Modal Regression.

A local modal estimation procedure is proposed for the regression function in a non-parametric regression model. A distinguishing characteristic of the proposed procedure is that it introduces an additional tuning parameter that is automatically selected using the observed data in order to achieve both robustness and efficiency of the resulting estimate. We demonstrate both theoretically and em...

Local Descriptors for Spatio-temporal Recognition

This paper presents and investigates a set of local spacetime descriptors for representing and recognizing motion patterns in video. Following the idea of local features in the spatial domain, we use the notion of space-time interest points and represent video data in terms of local space-time events. To describe such events, we define several types of image descriptors over local spatio-tempor...

On the Robust Modal Local Polynomial Regression

Modal local polynomial regression uses double kernel as the loss function to gain some robustness in the nonparametric regression. Current researches use the standard normal density function as the weight function to down-weigh the influences from the outliers. This paper extends the standard normal weight function to a general class weight functions. All the theoretical properties found by usi...

The Support Vector Machine for Nonlinear Spatio-Temporal Regression

Due to the increasingly demand for spatio-temporal analysis, time series and spatial statistics are extended to the spatial dimension and the temporal dimension respectively or they are combined via linear regression. However, such linear regression is just a simplification of complicated spatio-temporal associations existing in complex geographical phenomena. In this study, the Support Vector ...

Multi - Dimensional Modal Logi as a Framework for Spatio - Temporal