Mark S. Kaiser

1.4k total citations
48 papers, 923 citations indexed

About

Mark S. Kaiser is a scholar working on Statistics and Probability, Environmental Engineering and Economics and Econometrics. According to data from OpenAlex, Mark S. Kaiser has authored 48 papers receiving a total of 923 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Statistics and Probability, 10 papers in Environmental Engineering and 8 papers in Economics and Econometrics. Recurrent topics in Mark S. Kaiser's work include Statistical Methods and Bayesian Inference (12 papers), Soil Geostatistics and Mapping (9 papers) and Spatial and Panel Data Analysis (6 papers). Mark S. Kaiser is often cited by papers focused on Statistical Methods and Bayesian Inference (12 papers), Soil Geostatistics and Mapping (9 papers) and Spatial and Panel Data Analysis (6 papers). Mark S. Kaiser collaborates with scholars based in United States, Taiwan and Japan. Mark S. Kaiser's co-authors include Noel Cressie, Petruţa C. Caragea, John R. Jones, Soumendra N. Lahiri, Paul L. Speckman, Nan‐Jung Hsu, Wayne J. Arendt, John Faaborg, Jeffrey J. Essner and Perry B. Hackett and has published in prestigious journals such as Journal of the American Statistical Association, PLoS ONE and Development.

In The Last Decade

Mark S. Kaiser

45 papers receiving 845 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark S. Kaiser United States 16 158 154 150 149 141 48 923
R. Husband United Kingdom 8 132 0.8× 47 0.3× 192 1.3× 35 0.2× 108 0.8× 11 1.8k
Chenhua Li China 17 133 0.8× 35 0.2× 337 2.2× 64 0.4× 77 0.5× 61 1.2k
Marek Omelka Czechia 20 263 1.7× 71 0.5× 205 1.4× 19 0.1× 295 2.1× 53 1.2k
Luís Carvalho United States 11 178 1.1× 59 0.4× 189 1.3× 148 1.0× 16 0.1× 29 883
Rosa M. Crujeiras Spain 16 52 0.3× 54 0.4× 71 0.5× 121 0.8× 128 0.9× 66 786
J. T. Gene Hwang United States 19 469 3.0× 74 0.5× 71 0.5× 89 0.6× 572 4.1× 49 1.8k
Giuliano Galimberti Italy 21 208 1.3× 56 0.4× 54 0.4× 22 0.1× 77 0.5× 58 1.3k
Ana Justel Spain 21 114 0.7× 78 0.5× 535 3.6× 86 0.6× 291 2.1× 43 1.5k
Snigdhansu Chatterjee United States 16 142 0.9× 121 0.8× 106 0.7× 53 0.4× 211 1.5× 62 1.4k
Robin K. S. Hankin New Zealand 18 25 0.2× 44 0.3× 90 0.6× 164 1.1× 102 0.7× 56 923

Countries citing papers authored by Mark S. Kaiser

Since Specialization
Citations

This map shows the geographic impact of Mark S. Kaiser'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 Mark S. Kaiser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark S. Kaiser more than expected).

Fields of papers citing papers by Mark S. Kaiser

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark S. Kaiser. 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 Mark S. Kaiser. The network helps show where Mark S. Kaiser may publish in the future.

Co-authorship network of co-authors of Mark S. Kaiser

This figure shows the co-authorship network connecting the top 25 collaborators of Mark S. Kaiser. A scholar is included among the top collaborators of Mark S. Kaiser 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 Mark S. Kaiser. Mark S. Kaiser 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.
Raich, James W., Mark S. Kaiser, Mathew E. Dornbush, Jonathan G. Martin, & Oscar J. Valverde‐Barrantes. (2023). Multiple factors co-limit short-term in situ soil carbon dioxide emissions. PLoS ONE. 18(2). e0279839–e0279839. 4 indexed citations
2.
Kaiser, Mark S., et al.. (2023). A subsampling perspective for extending the validity of state-of-the-art bootstraps in the frequency domain. Biometrika. 110(4). 1099–1115. 5 indexed citations
3.
4.
Nordman, Daniel J., et al.. (2021). Modeling Transitivity in Local Structure Graph Models. Sankhya A. 84(1). 389–417.
5.
Smith, Jamie, et al.. (2020). Home Blood Pressure Monitoring in Cases of Clinical Uncertainty to Differentiate Appropriate Inaction From Therapeutic Inertia. The Annals of Family Medicine. 18(1). 50–58. 8 indexed citations
6.
Kaiser, Mark S., et al.. (2019). Simulating Markov Random Fields With a Conclique-Based Gibbs Sampler. Journal of Computational and Graphical Statistics. 29(2). 286–296. 4 indexed citations
7.
Kaiser, Mark S., et al.. (2019). A Local Structure Graph Model: Modeling Formation of Network Edges as a Function of Other Edges. Political Analysis. 27(4). 397–414. 4 indexed citations
8.
Cai, Weijie, Mark S. Kaiser, & Jack C. M. Dekkers. (2011). Genetic analysis of longitudinal measurements of performance traits in selection lines for residual feed intake in Yorkshire swine1. Journal of Animal Science. 89(5). 1270–1280. 12 indexed citations
9.
Kaiser, Mark S. & Petruţa C. Caragea. (2008). Exploring Dependence with Data on Spatial Lattices. Biometrics. 65(3). 857–865. 14 indexed citations
10.
11.
Senchina, David S., et al.. (2005). Changes in immunomodulatory properties of Echinacea spp. root infusions and tinctures stored at 4 °C for four days. Clinica Chimica Acta. 355(1-2). 67–82. 28 indexed citations
12.
Zhu, Jun, Jens C. Eickhoff, & Mark S. Kaiser. (2003). Modeling the Dependence between Number of Trials and Success Probability in Beta‐Binomial–Poisson Mixture Distributions. Biometrics. 59(4). 955–961. 17 indexed citations
13.
Lee, Jaehyeong, Mark S. Kaiser, & Noel Cressie. (2001). Multiway Dependence in Exponential Family Conditional Distributions. Journal of Multivariate Analysis. 79(2). 171–190. 7 indexed citations
14.
Kaiser, Mark S. & Noel Cressie. (2000). The Construction of Multivariate Distributions from Markov Random Fields. Journal of Multivariate Analysis. 73(2). 199–220. 43 indexed citations
15.
Lahiri, Soumendra N., Mark S. Kaiser, Noel Cressie, & Nan‐Jung Hsu. (1999). Prediction of Spatial Cumulative Distribution Functions Using Subsampling. Journal of the American Statistical Association. 94(445). 86–97. 69 indexed citations
16.
Kaiser, Mark S., et al.. (1997). COMPARISON OF NON PARALLEL IMMUNOASSAY CURVES RESULTING FROM MIXTURES OF COMPETING ANTIGENS. Statistics in Medicine. 16(10). 1151–1166. 2 indexed citations
17.
Jergens, Albert E., Frances M. Moore, Mark S. Kaiser, Joseph S. Haynes, & Joann Μ. Kinyon. (1996). Morphometric evaluation of immunoglobulin A-containing and immunoglobulin G-containing cells and T cells in duodenal mucosa from healthy dogs and from dogs with inflammatory bowel disease or nonspecific gastroenteritis. American Journal of Veterinary Research. 57(5). 697–704. 42 indexed citations
18.
Kaiser, Mark S., Paul L. Speckman, & John R. Jones. (1994). Statistical Models for Limiting Nutrient Relations in Inland Waters. Journal of the American Statistical Association. 89(426). 410–423. 68 indexed citations
19.
Steadman, Bryan L., William A. Stubblefield, Thomas W. LaPoint, Harold L. Bergman, & Mark S. Kaiser. (1991). Decreased survival of rainbow trout exposed to no. 2 fuel oil caused by sublethal preexposure. Environmental Toxicology and Chemistry. 10(3). 355–363. 15 indexed citations
20.
Faaborg, John, Wayne J. Arendt, & Mark S. Kaiser. (1984). Rainfall correlates of bird population fluctuations in a Puerto Rican dry forest: A 10-year study. The Wilson Journal of Ornithology. 96(4). 575–593. 48 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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