A Varying Precision Beta Prime Autoregressive Moving Average Model With Application to Water Flow Data
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DOI: 10.1002/env.2886
Abstract: We introduce a dynamic model tailored for positively valued time series. It accommodates both autoregressive and moving average dynamics and allows for explanatory variables. The underlying assumption is that each random variable follows, conditional on… read more here.
Keywords: time; precision; autoregressive moving; moving average ... See more keywords
Closed‐Form Approximation of Stock‐Based Awards With Moving‐Average Vesting Conditions
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DOI: 10.1002/fut.22576
Abstract: A market‐based compensation award with a moving‐average condition becomes vested when the ‐days moving‐average stock price exceeds a predetermined threshold. The same mechanism applies to the economic characteristics of founder shares issued in connection with… read more here.
Keywords: moving average; based awards; form approximation; stock ... See more keywords
A multidimensional spatial lag panel data model with spatial moving average nested random effects errors
Sign Up to like & getrecommendations! Published in 2018 at "Empirical Economics"
DOI: 10.1007/s00181-017-1410-7
Abstract: This paper focuses on a three-dimensional model that combines two different types of spatial interaction effects, i.e. endogenous interaction effects via a spatial lag on the dependent variable and interaction effects among the disturbances via… read more here.
Keywords: spatial lag; spatial moving; moving average; model ... See more keywords
Moving average filtering with deconvolution (MAD) for hidden Markov model with filtering and correlated noise
Sign Up to like & getrecommendations! Published in 2019 at "European Biophysics Journal"
DOI: 10.1007/s00249-019-01368-1
Abstract: Ion channel data recorded using the patch clamp technique are low-pass filtered to remove high-frequency noise. Almanjahie et al. (Eur Biophys J 44:545–556, 2015) based statistical analysis of such data on a hidden Markov model… read more here.
Keywords: hidden markov; markov model; moving average; correlated noise ... See more keywords
Best Subset Selection for Double-Threshold-Variable Autoregressive Moving-Average Models: The Bayesian Approach
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DOI: 10.1007/s10614-021-10124-7
Abstract: In this paper, we propose an effective Bayesian subset selection method for the double-threshold-variable autoregressive moving-average (DT-ARMA) models. The usual complexity of estimation is increased mainly by capturing the correlation between two threshold variables and… read more here.
Keywords: threshold variable; moving average; double threshold; subset selection ... See more keywords
Nonparametric estimation for i.i.d. Gaussian continuous time moving average models
Sign Up to like & getrecommendations! Published in 2020 at "Statistical Inference for Stochastic Processes"
DOI: 10.1007/s11203-020-09228-y
Abstract: We consider a Gaussian continuous time moving average model $$X(t)=\int _0^t a(t-s)dW(s)$$ X ( t ) = ∫ 0 t a ( t - s ) d W ( s ) where W is a… read more here.
Keywords: moving average; time; nonparametric estimation; time moving ... 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
A Novel Moving Average Forecasting Approach Using Fuzzy Time Series Data Set
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Control, Automation and Electrical Systems"
DOI: 10.1007/s40313-019-00467-w
Abstract: In this study, we develop a novel moving average forecasting approach based on fuzzy time series data set. The main objective of applying this moving average approach in develop method is to provide better results… read more here.
Keywords: fuzzy time; moving average; series data; time series ... See more keywords
An integrated approach to optimize moving average rules in the EUA futures market based on particle swarm optimization and genetic algorithms
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DOI: 10.1016/j.apenergy.2016.01.045
Abstract: Climate change is a big challenge facing global community in 21st century. The carbon emission futures markets has been treated as a key tool to combat climate change cost-effectively. Making profits from futures trading is… read more here.
Keywords: eua futures; approach optimize; market; moving average ... See more keywords
Mean sea surface model over China seas and its adjacent ocean established with the 19-year moving average method from multi-satellite altimeter data
Sign Up to like & getrecommendations! Published in 2020 at "Continental Shelf Research"
DOI: 10.1016/j.csr.2019.104009
Abstract: Abstract A new mean sea surface (MSS) model (named Shandong University of Science and Technology (2018) (SUST2018) MSS model) with a grid of 1′ × 1′ over China seas and its adjacent ocean (0°N~41°N, 100°E~140°E) is established… read more here.
Keywords: moving average; model; satellite altimeter; year moving ... See more keywords
Hierarchically spatial autoregressive and moving average error model
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DOI: 10.1016/j.econmod.2018.06.022
Abstract: This paper considers a hierarchically spatial autoregressive and moving average error (HSEARMA) model. This model captures the spatially autoregressive and moving average error correlation, the county-level random effects, and the district-level random effects nested within… read more here.
Keywords: moving average; autoregressive moving; hierarchically spatial; average error ... See more keywords