[PDF] Top 20 Factor modeling for high dimensional time series

... functional time series has been of a more theoretical nature; see ...functional series (Part IV of Ferraty & Vieu ...curve series in this chapter, the methodology may be extended to a more ... See full document

... better modeling and ...for time series though they can work well for static ...linear time series is carried out to show why they ...nonlinear time series, the proposed ... See full document

... and are plotted against the observed runoff in fig. 5.6. From the runoff forecast graph it is obvious that the model depicts a good agreement with the runoff pattern however, runoff quantities are over predictive during ... See full document

... [9] series define the standard for electric con- nectors and their charging system architecture, including physical, electrical, communication protocol, and per- formance ... See full document

... Background: Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be ... See full document

... conventional time series are represented by a vector whose i-th element are a value at the i-th time, therefore the value can also be used as a local feature; and 2) as in some types of time ... See full document

... The above model selection procedure can be seen as the nonparametric kernel extension of the SIS method introduced by Fan and Lv (2008) in the context of linear regression models. Recent extensions to nonparametric ... See full document

... large dimensional data[82, 81, 83]. In low dimensional settings, there have been remark- able parametric and nonparametric nonlinear time series models that have been applied successfully to ... See full document

... of time series models are also able to capture more than only approx- imations in the mean ...of time series models may be able to provide not only good approximations for the conditional-mean ... See full document

... a time-varying covariance matrix ...single time-constant smoothing parameter 0 < < 1, with extensions to accommodate locally varying smoothness not straightforward due to the need to maintain positive ... See full document

... committee of physician in the study. In cases where the physician faces a great number of possible decisions, the recommendations would narrow down the size of prescription candidates. On the other hand, the machine ... See full document

... operated and crushed sugarcane billets at 24 hours per day where there was a feed elevator to convey billets for processing plant. The plant was experiencing heavy queues and therefore each cart has to wait in a ... See full document

... of time-series of prices often follows stochastic and chaos ...the modeling and prediction of the economic ...the modeling of stock prices in terms of a geometrical motion stochastic ... See full document

... a high demand for hospital information collected and stored, when one region discovered this virus, we can search around their nearest hospital, shorten its carriers turnaround time for timely treatment of ... See full document

... the time series segmentation problem as an application of sparse modelling and estimation, since the breakpoints in the dependence structure of the time series are often assumed to be ... See full document

... Due to the nature of the motion capture process, which can be adversely affected by lighting and environmental effects, as well as noise during recording, motion capture data often contains missing or unusable data. Some ... See full document

... There are many tools to develop large-scale workflows from both the HPC and Big Data communities. Some noteworthy examples of HPC workflows include Tavarna [18], Kepler [19] and Airavata [20]. These tools are geared ... See full document

... [34]. High-dimensional time series arise in various scientific contexts, such as in recordings of brain activity from numerous regions of the brain [36] or financial time series ... See full document

... resenting series in frequency domain can expose the periodicities of the series and can aid in understanding the data generating ...of high orders, more data is usually needed to get reli- able ...a ... See full document

... changepoint to determine the subset of variables each changepoint affects. As estimation is not performed jointly, in that the changepoints and affected variables are not estimated at the same time the methods are ... See full document