Adaptive piecewise polynomial estimation via trend filtering
نویسندگان
چکیده
منابع مشابه
Adaptive Piecewise Polynomial Estimation via Trend Filtering
We study trend filtering, a recently proposed tool of Kim et al. (2009) for nonparametric regression. The trend filtering estimate is defined as the minimizer of a penalized least squares criterion, in which the penalty term sums the absolute kth order discrete derivatives over the input points. Perhaps not surprisingly, trend filtering estimates appear to have the structure of kth degree splin...
متن کاملFiltering Motion Data Through Piecewise Polynomial Approximation
In this work we propose a system to filter human movement data and store them into a compact representation. We are interested both in noise reduction and in segmentation. The method described in this paper relies on a iterative optimization and guarantee to converge to a local optimum: it proved anyway to produce stable results and to provide an accurate segmentation on the analyzed data . We ...
متن کاملAdaptive Estimation of Directional Trend
Consider a one-way layout with one directional observation per factor level. Each observed direction is a unit vector in R measured with random error. Information accompanying the measurements suggests that the mean directions, normalized to unit length, follow a trend: the factor levels are ordinal and mean directions at nearby factor levels may be close. Measured positions of the paleomagneti...
متن کاملTrend filtering via empirical mode decompositions
The problem of filtering low-frequency trend from a given time series is considered. In order to solve this problem, a nonparametric technique called empirical mode decomposition trend filtering is developed. A key assumption is that the trend is representable as the sum of intrinsic mode functions produced by the empirical mode decomposition (EMD) of the time series. Based on an empirical anal...
متن کاملAdaptive Filtering Via
This paper introduces the application of particle swarm optimization techniques to generalized adaptive nonlinear and reeursive fdter structures. Particle swarm optimization (PSO) is a population based optimization algorithm, similar to the genetic algorithm (GA), that performs a struetored randomized search of an unknown parameter space by manipulating a population of parameter estimates to co...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2014
ISSN: 0090-5364
DOI: 10.1214/13-aos1189