Functional time series
Grouped multivariate and functional time series forecasting: an application to annuity pricing
... grouped functional time series methods (Shang and Hyndman 2017) to reconcile age-specific mortality ...grouped functional time series forecasting methods to multivariate ...
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The Common Principal Component (CPC) Approach to Functional time Series (FTS) Models
... a functional time series model for the entire aggregate of groups (the product term) and functional time series models for each of the ratio terms of group-specific rates to the ...
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Grouped multivariate and functional time series forecasting: an application to annuity pricing
... grouped functional time series methods (Shang, Han and Rob ...grouped functional time series forecasting methods to multivariate time series and apply them to ...
28
Measuring Global Warming: Global and Hemisphere Mean Temperature Anomalies Predictions Using Sliced Functional Time Series (SFTS) Model
... In this study, the sliced functional time series (SFTS) model is applied to the Global, Northern and Southern temperature anomalies. We obtained the combined land-surface air and sea-surface water ...
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Forecasting Inflation using Functional Time Series Analysis
... In every real life phenomenon there is an uncertainty involved. We want to model this uncertainty for some reasons. One of the reason is forecasting for the purpose of decision making. If we have some knowledge of the ...
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Predicting Breast Cancer Incidence Rates Among White and Black Women in the United States: An Application of FTS Model
... In order to analyze the incidence rates and to describe the changes in incidence rates with age, we also plot the incidence curves (as function of age) for the years 1973-2013 in Figure 2. The observed log incidence ...
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Time series modeling and decomposition
... In another study, Dagum and Bianconcini (2008) derive two density functions and corresponding orthonormal polynomials to obtain two Reproducing Kernel Hilbert Space representations which give excellent results for ...
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Forecasting of Rainfall in Pakistan via Sliced Functional Times Series (SFTS)
... sliced functional time series (SFTS) model, a relatively new method of forecasting was introduced and the monthly forecasts for the next ten years (2016-2025) were obtained along with 80% prediction ...
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Functional GARCH models: the quasi likelihood approach and its applications
... financial time series and their importance for the financial industry, it is desirable to provide corresponding models and adequate statistical methodology for data that are given at a higher ...of ...
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Data Abstraction for Visualizing Large Time Series
... Numeric time series is a class of data consisting of chronologically ordered observations represented by numeric ...for time series ...on time series mining and visualization, ...
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DeepFMRI: And End-to-End Deep Network for Classification of FRMI Data
... correlation-based functional connectivity results and clustering based ...results, functional connectivity is calculated through correlation, followed by the elastic net as feature se- lection and an SVM as ...
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On the Variance of Antithetic Time Series
... Before antithetic combining can correct bias in a time series model, bias must first occur. Bias occurs when a sample of data is observed, an autoregressive model is fitted to the data, and there is failure ...
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Functional Modelling of Microarray Time Series
... individual time series, across all genes and individuals, (b) accounting for the correlation between individu- als on a gene by gene basis and (c) modelling the correlation between ...standard time ...
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Empirical Analysis of Time Series
... the time dependence of the gate voltage VG or the gate current ...(the time resolution) of VG(t), the results were found to be robust : the amplitude of the fluctuations were only multiplied by a constant ...
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Time Series Motifs in Practice.
... Anomaly, intrusion or discord detection are general terms that address the problem of finding any unusual patterns, activity or behavior that do not fit the normal and ex- pected behaviors in some data stream. A variety ...
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On categorical time series with covariates
... categorical time series that might include some covariates which are not necessarily ...Binary time series are particular cases of a categorical time series and the results we ...
25
A Comparative Simulation Study of ARIMA and Fuzzy Time Series Model for Forecasting Time Series Data
... or time consuming to gather and it involves generating data set by specific statistical model or using random ...Fuzzy Time Series (FTS) model in order to identify the best model for forecasting ...
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Power Spectral Density Analysis of Time Series of Pixel of Functional Magnetic Resonance Image for Different Motor Activity
... The Fourier transform reflects the strength (or power) of the signal at each frequency. When the power is plotted across all frequencies, this plot is referred to as a power spectrum. Power spectra are commonly used in ...
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Comparison of exponential time series alignment and time series alignment using artificial neural networks by example of prediction of future development of stock prices of a specific company
... For comparison, we used the neural network number 4 and 5, in particular MLP 1-20-1 and MLP 1-17-1, in addition to prediction using exponential time series alignment. Both neural networks predict constant ...
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Functional quantitative susceptibility mapping (fQSM)
... phase time-series to the functional paradigm, in the case where no complex temporal and spatial filtering nor QSM calculation were applied in the phase processing pipeline ...the time needed ...
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