Forecasting in nonlinear univariate time series using penalized splines
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DOI: 10.1007/s00362-015-0711-1
Abstract: In this article we discuss penalized splines for fitting and forecasting univariate nonlinear time series models. While penalized splines have been excessively used in smooth regression, their use in nonlinear time series models is less… read more here.
Keywords: time series; penalized splines; time; series models ... See more keywords
Ability Assessment of the Stationary and Cyclostationary Time Series Models to Predict Drought Indices
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DOI: 10.1007/s11269-020-02710-5
Abstract: Drought forecasting and monitoring play a significant role in reducing the negative effects of global meteorological droughts caused by different intensities at different temporal and spatial scales in different regions, especially in regions with high… read more here.
Keywords: time series; best fitted; moving average; series models ... See more keywords
Maintenance scheduling using data mining techniques and time series models
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DOI: 10.1080/17509653.2017.1314201
Abstract: Abstract Condition-based maintenance (CBM) should be derived carefully to reduce maintenance costs along with useless maintenance shifts and to predict ideal time to do the maintenance. In this paper, a new method is proposed by… read more here.
Keywords: data mining; time series; maintenance; time ... See more keywords
Asymptotic properties of quasi-maximum likelihood estimators in observation-driven time series models
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DOI: 10.1214/17-ejs1299
Abstract: We study a general class of quasi-maximum likelihood estimators for observation-driven time series models. Our main focus is on models related to the exponential family of distributions like Poisson based models for count time series… read more here.
Keywords: time series; maximum likelihood; time; series models ... See more keywords
Mixed Models as a Tool for Comparing Groups of Time Series in Plant Sciences
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DOI: 10.3390/plants10020362
Abstract: Plants adapt to continual changes in environmental conditions throughout their life spans. High-throughput phenotyping methods have been developed to noninvasively monitor the physiological responses to abiotic/biotic stresses on a scale spanning a long time, covering… read more here.
Keywords: time series; time; series models; mixed models ... See more keywords
Sequential change-point detection in time series models based on pairwise likelihood
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DOI: 10.5705/ss.202015.0359
Abstract: The paper proposes a sequential monitoring scheme for detecting changes in parameter values for general time series models using pairwise likelihood. Under this scheme, a change-point is declared when the cumulative sum of the first… read more here.
Keywords: series models; pairwise likelihood; scheme; time series ... See more keywords