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Found 17 dataset(s) matching "Autoregressive model".
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In the literature, impulsive signals are mostly modeled by symmetric alpha-stable processes. To represent their temporal dependencies, usually autoregressive models with time-invariant...
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We present a novel and general methodology for modeling time-varying vector autoregressive processes which are widely used in many areas such as modeling of chemical processes, mobile...
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We applied machine learning (ML) models to forecast streamflow drought from 1 to 13 weeks into the future at more than 3,000 streamgage locations across the Conterminous United States. We applied...
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In this work, we present a novel method for modeling time-varying autoregressive impulsive signals driven by symmetric alpha stable distributions. The proposed method can be interpreted as a...
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<p>A set of programs for best prediction of lactation yields.</p> <p>Lactation records of any reasonable length now can be processed with the selection index method known as best prediction (BP)....
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This data in publicly available environmental data that showcases the spmodel R package.
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Background We examined whether quarterly patient enrollment in a large multicenter clinical trials group could be modeled in terms of predictors including time parameters (such as...
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Andrews Meadow in the Loch Vale watershed, Rocky Mountain National Park. Sample Collection: Englemann spruce (Picea engelmannii) living on slopes surrounding and at the edge of Andrews meadow...
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This data release includes estimates of annual and daily concentrations and fluxes for nitrate plus nitrite, total phosphorus, and suspended sediment for two sites in the Upper Macoupin Creek...
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This paper is about applying recurrent least squares support vector machines (LS-SVM) on three ESTSP08 competition datasets. Least squares support vector machines are used as nonlinear models...
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Data set used to estimate the autoregressive distributed lag (ADL) model to understand how water quality measures (e.g., raw water TOC and algal toxin) and other variables affect drinking water...
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contains all satellite, pm2.5, and meteorological data used in statistical modeling effort to improve prediction of pm2.5. This dataset is associated with the following publication: Schliep, E.,...
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ArcGIS raster maps for the wildfire risk and tree loss probability in the United Stated for the paper "Estimating climate-sensitive wildfire risk and tree mortality models for use in broad-scale...
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The asci files are the probability of the NDVI trend (slope) and the direction of the NDVI trend (+/-). These files can be mapped in ArcMap using ArcToolbox (conversion tools and asci to raster)....
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<p><br></p> <p>[NOTE - 11/24/2021: this dataset supersedes an earlier version <a href="https://doi.org/10.15482/USDA.ADC/1518654" target="_blank">https://doi.org/10.15482/USDA.ADC/1518654</a>...
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In the last decade alpha-stable distributions have become a standard model for impulsive data. Especially the linear symmetric alpha-stable processes have found applications in various fields....
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Harmful algal blooms (HABs) have recently been observed in rivers, including the Illinois River in the Midwest United States. The Illinois River Basin has a history of eutrophication issues,...
