Zobrazeno 1 - 10
of 108
pro vyhledávání: '"Nunes, Matthew"'
The TrendLSW R package has been developed to provide users with a suite of wavelet-based techniques to analyse the statistical properties of nonstationary time series. The key components of the package are (a) two approaches for the estimation of the
Externí odkaz:
http://arxiv.org/abs/2406.05012
Accurate forecasting of the U.K. gross value added (GVA) is fundamental for measuring the growth of the U.K. economy. A common nonstationarity in GVA data, such as the ABML series, is its increase in variance over time due to inflation. Transformed o
Externí odkaz:
http://arxiv.org/abs/2303.07772
In this article we focus on dynamic network data which describe interactions among a fixed population through time. We model this data using the latent space framework, in which the probability of a connection forming is expressed as a function of lo
Externí odkaz:
http://arxiv.org/abs/2112.10220
Modelling Time-Varying First and Second-Order Structure of Time Series via Wavelets and Differencing
Publikováno v:
Electronic Journal of Statistics (2022) 16(2): 4398-4448
Most time series observed in practice exhibit time-varying trend (first-order) and autocovariance (second-order) behaviour. Differencing is a commonly-used technique to remove the trend in such series, in order to estimate the time-varying second-ord
Externí odkaz:
http://arxiv.org/abs/2108.07550
Industrial cyber-physical systems (ICPSs) manage critical infrastructures by controlling the processes based on the "physics" data gathered by edge sensor networks. Recent innovations in ubiquitous computing and communication technologies have prompt
Externí odkaz:
http://arxiv.org/abs/2101.03564
Deciding which predictors to use plays an integral role in deriving statistical models in a wide range of applications. Motivated by the challenges of predicting events across a telecommunications network, we propose a semi-automated, joint model-fit
Externí odkaz:
http://arxiv.org/abs/2001.02883
This article introduces the GNAR package, which fits, predicts, and simulates from a powerful new class of generalised network autoregressive processes. Such processes consist of a multivariate time series along with a real, or inferred, network that
Externí odkaz:
http://arxiv.org/abs/1912.04758
Publikováno v:
In Computational Statistics and Data Analysis March 2023 179
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Distributed acoustic sensing technology is increasingly being used to support production and well management within the oil and gas sector, for example to improve flow monitoring and production profiling. This sensing technology is capable of recordi
Externí odkaz:
http://arxiv.org/abs/1809.09729