Nancy L. Garcia

878 citations
53 papers · 409 indexed · h-index 12

Nancy L. Garcia

47 papers receiving 375 citations

Peers

Nancy L. Garcia
Comparison fields: 5 of 99
  • Statistics and Probability 104
  • Mathematical Physics 87
  • Applied Mathematics 40
  • Insect Science 47
  • Analytical Chemistry 28
Replace C. R. Rao with:
C. R. Rao China
Federico Bassetti Italy
A. A. Rayner South Africa
Jakob Gulddahl Rasmussen Denmark
Mark C. Wilson New Zealand
C.M. Triggs New Zealand
Yonatan Bilu Israel
Ron Evans United States
Burton Simon United States
Nancy L. Garcia relative to C. R. Rao China C. R. Rao's profile →
Citations per field
00.5×10×14.5×
C. R. Rao · 1×
Citations per year

Countries citing papers authored by Nancy L. Garcia

Since Specialization
Citations

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

Fields of papers citing papers by Nancy L. Garcia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nancy L. Garcia. 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 Nancy L. Garcia. The network helps show where Nancy L. Garcia may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Nancy L. Garcia, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nancy L. Garcia Line = papers co-authored together Nancy L. Garcia links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20230
3
mrf2d: Markov random field image models in R
20200
4 20152
5 20146
6 20133
7
A general context-tree-based approach to perfect simulation for chains of infinite order
20111
8 201113
9 20070
10 20062
11 20061
12 20053
13 20037
14 200249
15 20018
16 200112
17 200114
18 20011
19
Perfect simulation of spatial processes
20006
20 199915

About Nancy L. Garcia

Nancy L. Garcia is a scholar working on Statistics and Probability, Mathematical Physics and Statistics, Probability and Uncertainty, having authored 53 papers that have together received 409 indexed citations. Recurring topics across this work include Stochastic processes and statistical mechanics (11 papers), Statistical Methods and Inference (9 papers), Bayesian Methods and Mixture Models (7 papers), Insect Pest Control Strategies (6 papers), Markov Chains and Monte Carlo Methods (6 papers), Algorithms and Data Compression (5 papers), Insect and Pesticide Research (4 papers) and Physiological and biochemical adaptations (4 papers). The work is most often cited by research in Statistics and Probability (104 citations), Mathematical Physics (87 citations) and Applied Mathematics (40 citations). Nancy L. Garcia has collaborated with scholars based in Brazil, United States and Venezuela. Frequent co-authors include Jacqueline Fleming, Pablo A. Ferrari, Maria Luiza S. Mello, José Luis Palacios, Roberto Fernández, Antonio Galves, César Hervás‐Martínez, Emiliano J. de Pedro Sanz, Klaus L. P. Vasconcellos and Tiffany L. Kinnibrugh. Their work appears in journals such as Technometrics, Journal of Econometrics and Journal of Statistical Software.

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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