Ray D. Nelson

2.7k total citations · 1 hit paper
21 papers, 2.0k citations indexed

About

Ray D. Nelson is a scholar working on Economics and Econometrics, Finance and Artificial Intelligence. According to data from OpenAlex, Ray D. Nelson has authored 21 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Economics and Econometrics, 5 papers in Finance and 5 papers in Artificial Intelligence. Recurrent topics in Ray D. Nelson's work include Fiscal Policy and Economic Growth (4 papers), Neural Networks and Applications (4 papers) and Financial Risk and Volatility Modeling (4 papers). Ray D. Nelson is often cited by papers focused on Fiscal Policy and Economic Growth (4 papers), Neural Networks and Applications (4 papers) and Financial Risk and Volatility Modeling (4 papers). Ray D. Nelson collaborates with scholars based in United States. Ray D. Nelson's co-authors include Jerry L. Hintze, James V. Hansen, James B. McDonald, Gary C. Cornia, Richard J. Butler, Rulon D. Pope, Robert A. Collins, Scott D. Grimshaw and Lawrence C. Walters and has published in prestigious journals such as Management Science, The Review of Economics and Statistics and Neurocomputing.

In The Last Decade

Ray D. Nelson

21 papers receiving 1.9k citations

Hit Papers

Violin Plots: A Box Plot-Density Trace Synergism 1998 2026 2007 2016 1998 250 500 750 1000

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Ray D. Nelson United States 12 317 221 196 181 148 21 2.0k
S. L. Singapore 7 440 1.4× 148 0.7× 162 0.8× 119 0.7× 357 2.4× 9 2.0k
Michael R. Chernick United States 27 234 0.7× 238 1.1× 221 1.1× 186 1.0× 458 3.1× 67 3.4k
Alvin C. Rencher United States 21 405 1.3× 195 0.9× 171 0.9× 219 1.2× 489 3.3× 32 3.7k
R. A. Johnson United States 20 439 1.4× 155 0.7× 89 0.5× 126 0.7× 183 1.2× 68 2.8k
Andrew A. Neath United States 11 392 1.2× 177 0.8× 146 0.7× 125 0.7× 550 3.7× 31 2.3k
Alexander J. Collins United Kingdom 9 257 0.8× 140 0.6× 124 0.6× 138 0.8× 356 2.4× 16 2.5k
Larry Rabinowitz United States 4 367 1.2× 106 0.5× 147 0.8× 136 0.8× 206 1.4× 5 2.4k
J. Brian Gray United States 15 178 0.6× 224 1.0× 161 0.8× 153 0.8× 470 3.2× 33 2.7k
Richard L. Scheaffer United States 23 363 1.1× 223 1.0× 213 1.1× 260 1.4× 622 4.2× 77 3.8k
W. Alan Nicewander United States 17 383 1.2× 104 0.5× 327 1.7× 173 1.0× 305 2.1× 37 3.4k

Countries citing papers authored by Ray D. Nelson

Since Specialization
Citations

This map shows the geographic impact of Ray D. Nelson's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ray D. Nelson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ray D. Nelson more than expected).

Fields of papers citing papers by Ray D. Nelson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ray D. Nelson. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ray D. Nelson. The network helps show where Ray D. Nelson may publish in the future.

Co-authorship network of co-authors of Ray D. Nelson

This figure shows the co-authorship network connecting the top 25 collaborators of Ray D. Nelson. A scholar is included among the top collaborators of Ray D. Nelson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Ray D. Nelson. Ray D. Nelson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Cornia, Gary C., Scott D. Grimshaw, Ray D. Nelson, & Lawrence C. Walters. (2010). The Effect of Local Option Sales Taxes on Local Sales. Public Finance Review. 38(6). 659–681. 10 indexed citations
2.
Cornia, Gary C. & Ray D. Nelson. (2010). State Tax Revenue Growth and Volatility. RePEc: Research Papers in Economics. 23–58. 21 indexed citations
3.
Cornia, Gary C., et al.. (2004). Fiscal Planning, Budgeting, and Rebudgeting Using Revenue Semaphores. Public Administration Review. 64(2). 164–179. 26 indexed citations
4.
Cornia, Gary C. & Ray D. Nelson. (2003). Special Report / Viewpoint Rainy Day Funds and Value at Risk. 1 indexed citations
5.
Hansen, James V. & Ray D. Nelson. (2003). Time-series analysis with neural networks and ARIMA-neural network hybrids. Journal of Experimental & Theoretical Artificial Intelligence. 15(3). 315–330. 24 indexed citations
6.
Hansen, James V. & Ray D. Nelson. (2002). Data mining of time series using stacked generalizers. Neurocomputing. 43(1-4). 173–184. 34 indexed citations
7.
Hansen, James V., James B. McDonald, & Ray D. Nelson. (1999). Time Series Prediction With Genetic‐Algorithm Designed Neural Networks: An Empirical Comparison With Modern Statistical Models. Computational Intelligence. 15(3). 171–184. 100 indexed citations
8.
Nelson, Ray D. & Rulon D. Pope. (1998). Improvements in the power of empirical stochastic dominance comparisons through kernel density estimation: a monte carlo study. Journal of Statistical Computation and Simulation. 60(4). 295–317. 2 indexed citations
9.
Hintze, Jerry L. & Ray D. Nelson. (1998). Violin Plots: A Box Plot-Density Trace Synergism. The American Statistician. 52(2). 181–184. 1180 indexed citations breakdown →
10.
Hintze, Jerry L. & Ray D. Nelson. (1998). Violin Plots: A Box Plot-Density Trace Synergism. The American Statistician. 52(2). 181–181. 284 indexed citations
11.
Hansen, James V. & Ray D. Nelson. (1997). Neural networks and traditional time series methods: a synergistic combination in state economic forecasts. IEEE Transactions on Neural Networks. 8(4). 863–873. 103 indexed citations
12.
McDonald, James B. & Ray D. Nelson. (1993). Beta estimation in the market model: skewness and leptokurtosis. Communication in Statistics- Theory and Methods. 22(10). 2843–2862. 9 indexed citations
13.
Nelson, Ray D. & Rulon D. Pope. (1991). Bootstrapped Insights into Empirical Applications of Stochastic Dominance. Management Science. 37(9). 1182–1194. 27 indexed citations
14.
Butler, Richard J., et al.. (1990). Robust and Partially Adaptive Estimation of Regression Models. The Review of Economics and Statistics. 72(2). 321–321. 75 indexed citations
15.
McDonald, James B. & Ray D. Nelson. (1989). Alternative beta estimation for the market model using partially adaptive techniques. Communication in Statistics- Theory and Methods. 18(11). 4039–4058. 24 indexed citations
16.
Nelson, Ray D., et al.. (1988). Forward and Futures Markets and the Competitive Firm under Price Uncertainty. Southern Economic Journal. 55(1). 182–182. 11 indexed citations
17.
Collins, Robert A. & Ray D. Nelson. (1986). The Interyear Effect of Routine Marketing on Farm Income and Utility. North Central Journal of Agricultural Economics. 8(2). 257–257. 2 indexed citations
18.
Nelson, Ray D.. (1985). Forward and Futures Contracts as Preharvest Commodity Marketing Instruments. American Journal of Agricultural Economics. 67(1). 15–23. 22 indexed citations
19.
Nelson, Ray D. & Robert A. Collins. (1985). A measure of hedging's performance. Journal of Futures Markets. 5(1). 45–55. 10 indexed citations
20.
Nelson, Ray D.. (1981). Should commercial grain farmers use futures markets to hedge against price risk. University Microfilms International eBooks. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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