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三亚国际数学论坛：Complex Time Series Modelling and Forecasting
三亚国际数学论坛 Complex Time Series Modelling Forecasting
2017/11/24
The purpose of this workshop is to bring together the leading experts, active scholars and young researchers in Dynamic Network, Spatio-Temporal Processes, and Functional Time Series under the umbrell...
Periodic Time Series Data Analysis.
Wavelet neural networks for nonlinear time series analysis
Non Stationary-nonlinear Time Series Wavelet Networks
2010/9/27
A wavelet network is an important tool for analyzing time series especially when it is nonlinear and non-stationary. It takes advantage of high resolution of wavelets and learning and feed forward nat...
New method to estimate missing data by using the asymmetrical winsorized mean in a time series
Missing Data Winsorized mean Neyman Allocation
2010/9/14
In this paper we consider the problem of missing data in a time series analysis. We propose asymmetrical r = s winsorized mean to handle the problem of missing data. Beside that we suggested the Neym...
Nonlinear Time Series Analysis Since 1990: Some Personal Reflections
Chaos common structure curse of dimensionality
2007/12/11
I reflect upon the development of nonlinear time series analysis since 1990 by focusing on five major areas of development. These areas include the interface between nonlinear time series analysis and...
PERCENTAGE POINTS AND POWER OF AK-S TYPE TEST FOR LINEARITY IN AUTOREGRESSIVE TIME SERIES
Kolmogorov-Smirnov type test
2007/12/10
The empirical upper percentage points of the null distribution of a Kolmogorov-Smirnov type test for checking linearity in autoregressive models are tabulated in this paper, and the good power propert...