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Showing 1 to 5 of 5 for “"Functional principal components."”.
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Modeling daily electricity load curve using cubic splines and functional principal components
… for a future month. The last approach uses functional principal components to model the daily electricity load profile for each day as a linear combination of three eigenfunctions, with the coefficients of the day-specific linear combinations modeled as univariate time series using transfer …
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Contributions to Functional Data Analysis
Functional data consist of repeated measurements taken over time for each subject. The data for a subject are assumed to be values of a random function that is observed at a discrete time points rather than a sequence of individual measurements. Functional data are classified dense or sparse based …
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Shape based classification and functional forecast of traffic flow profiles
… estimates of model parameters.</p><p>Lastly, a functional time series approach was proposed to forecast traffic flow for short and medium-term horizons. It is based on functional principal components decomposition to forecast three different traffic scenarios. Real-time forecast scenarios of …
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Bayesian analysis of historical functional linear models with application to air pollution forecasting
Historical functional linear models are used to analyse the relationship between a functional response and a functional predictor whereby only the past of the predictor process can affect the current outcome. In this work, we develop a Bayesian framework for the analysis of the historical …
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Applications of functional data analysis to environmental problems.
Functional Data Analysis (FDA) is a relatively recent framework within the statistical sciences, and while it offers compelling benefits to many applications, it has not yet gained widespread applied use. Two important environmental applications, water quality profile forecasting and larval fish …