Fernanda De Bastiani

1.3k total citations
34 papers, 798 citations indexed

About

Fernanda De Bastiani is a scholar working on Environmental Engineering, Economics and Econometrics and Statistics and Probability. According to data from OpenAlex, Fernanda De Bastiani has authored 34 papers receiving a total of 798 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Environmental Engineering, 10 papers in Economics and Econometrics and 10 papers in Statistics and Probability. Recurrent topics in Fernanda De Bastiani's work include Soil Geostatistics and Mapping (15 papers), Spatial and Panel Data Analysis (9 papers) and Soil and Land Suitability Analysis (6 papers). Fernanda De Bastiani is often cited by papers focused on Soil Geostatistics and Mapping (15 papers), Spatial and Panel Data Analysis (9 papers) and Soil and Land Suitability Analysis (6 papers). Fernanda De Bastiani collaborates with scholars based in Brazil, Chile and Australia. Fernanda De Bastiani's co-authors include Robert A. Rigby, Mikis D. Stasinopoulos, Gillian Z. Heller, Vlasios Voudouris, Miguel Ángel Uribe-Opazo, Manuel Galea, Renata M.C.R. de Souza, Jerry Adriani Johann, Karis Tenneson and Alberto Barretto and has published in prestigious journals such as The Science of The Total Environment, Expert Systems with Applications and The American Statistician.

In The Last Decade

Fernanda De Bastiani

31 papers receiving 781 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fernanda De Bastiani Brazil 11 191 124 119 113 83 34 798
Vlasios Voudouris United Kingdom 12 112 0.6× 75 0.6× 188 1.6× 68 0.6× 31 0.4× 28 708
Nadja Klein Germany 15 307 1.6× 65 0.5× 152 1.3× 89 0.8× 40 0.5× 73 790
Nikolaus Umlauf Austria 16 152 0.8× 84 0.7× 107 0.9× 313 2.8× 73 0.9× 33 788
Magnus Ekström Sweden 17 136 0.7× 136 1.1× 40 0.3× 182 1.6× 77 0.9× 55 731
Mikis D. Stasinopoulos United Kingdom 8 150 0.8× 27 0.2× 59 0.5× 100 0.9× 55 0.7× 14 724
Natalya Pya Kazakhstan 5 105 0.5× 50 0.4× 39 0.3× 127 1.1× 118 1.4× 8 611
T. Goicoa Spain 21 284 1.5× 79 0.6× 345 2.9× 87 0.8× 40 0.5× 61 1.1k
José A. Vilar Spain 18 66 0.3× 46 0.4× 308 2.6× 133 1.2× 112 1.3× 56 1.0k
Solomon W. Harrar United States 16 289 1.5× 31 0.3× 34 0.3× 51 0.5× 62 0.7× 52 907
Benjamin Säfken Germany 8 73 0.4× 44 0.4× 32 0.3× 97 0.9× 103 1.2× 23 567

Countries citing papers authored by Fernanda De Bastiani

Since Specialization
Citations

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

Fields of papers citing papers by Fernanda De Bastiani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fernanda De Bastiani. 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 Fernanda De Bastiani. The network helps show where Fernanda De Bastiani may publish in the future.

Co-authorship network of co-authors of Fernanda De Bastiani

This figure shows the co-authorship network connecting the top 25 collaborators of Fernanda De Bastiani. A scholar is included among the top collaborators of Fernanda De Bastiani 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 Fernanda De Bastiani. Fernanda De Bastiani 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.
Foroni, Francesco, Fernando Marmolejo‐Ramos, Rand R. Wilcox, Fernanda De Bastiani, & Gün R. Semin. (2023). A multi‐analyses approach of inductive/deductive asymmetry in the affective priming paradigm. British Journal of Psychology. 114(3). 550–565.
2.
Uribe-Opazo, Miguel Ángel, et al.. (2023). Spatial variability of wheat yield using the gaussian spatial linear model. Australian Journal of Crop Science. 179–189. 2 indexed citations
3.
Bastiani, Fernanda De, et al.. (2022). Selection Criterion of Working Correlation Structure for Spatially Correlated Data. The American Statistician. 77(3). 283–291. 1 indexed citations
4.
Souza, Renata M.C.R. de, et al.. (2022). Exploratory spatial analysis for interval data: A new autocorrelation index with COVID-19 and rent price applications. Expert Systems with Applications. 195. 116561–116561. 16 indexed citations
5.
Marmolejo‐Ramos, Fernando, Zeinab Fazlali, Detlef Wegener, et al.. (2022). Generalised exponential-Gaussian distribution: a method for neural reaction time analysis. Cognitive Neurodynamics. 17(1). 221–237. 13 indexed citations
6.
Carvalho, Daniel, et al.. (2021). Spatial scan statistics based on empirical likelihood. Communications in Statistics - Simulation and Computation. 52(8). 3897–3911.
7.
Bastiani, Fernanda De, et al.. (2021). Aspectos espacial e temporal e fatores associados à interiorização da Covid-19 em Pernambuco, Brasil. Ciência & Saúde Coletiva. 26(6). 2171–2182. 9 indexed citations
8.
Uribe-Opazo, Miguel Ángel, et al.. (2021). Spatial-temporal Analysis of Soybean Productivity Using Geostatistical Methods. Journal of Agricultural Studies. 9(2). 283–283. 2 indexed citations
9.
Uribe-Opazo, Miguel Ángel, et al.. (2020). Influence diagnostics on a reparameterized t-Student spatial linear model. Spatial Statistics. 41. 100481–100481. 6 indexed citations
10.
11.
Fendrich, Arthur Nicolaus, Alberto Barretto, Vinícius Guidotti, et al.. (2020). Disclosing contrasting scenarios for future land cover in Brazil: Results from a high-resolution spatiotemporal model. The Science of The Total Environment. 742. 140477–140477. 20 indexed citations
12.
Uribe-Opazo, Miguel Ángel, et al.. (2019). GEOSTATISTICAL MODELING OF SOYBEAN YIELD AND SOIL CHEMICAL ATTRIBUTES USING SPATIAL BOOTSTRAP. Engenharia Agrícola. 39(3). 350–357. 3 indexed citations
13.
Uribe-Opazo, Miguel Ángel, et al.. (2018). GAUSSIAN SPATIAL LINEAR MODEL OF SOYBEAN YIELD USING BOOTSTRAP METHODS. Engenharia Agrícola. 38(1). 110–116. 7 indexed citations
14.
Nicolis, Orietta, et al.. (2018). Statistical methods for identifying anisotropy in the Spodoptera frugiperda spatial distribution. Spanish Journal of Agricultural Research. 16(1). e1003–e1003. 2 indexed citations
15.
Bastiani, Fernanda De, et al.. (2018). Case-deletion diagnostics for spatial linear mixed models. Spatial Statistics. 28. 284–303. 5 indexed citations
16.
Stasinopoulos, Mikis D., Robert A. Rigby, Gillian Z. Heller, Vlasios Voudouris, & Fernanda De Bastiani. (2017). Flexible regression and smoothing: using GAMLSS in R. CERN Document Server (European Organization for Nuclear Research). 124 indexed citations
17.
Bastiani, Fernanda De, et al.. (2017). Gaussian spatial linear models with repetitions: An application to soybean productivity. Spatial Statistics. 21. 319–335. 5 indexed citations
18.
Bastiani, Fernanda De, et al.. (2016). Gaussian Markov random field spatial models in GAMLSS. Journal of Applied Statistics. 45(1). 168–186. 18 indexed citations
19.
Richetti, Jonathan, Miguel Ángel Uribe-Opazo, Fernanda De Bastiani, & Jerry Adriani Johann. (2016). TÉCNICAS PARA DETECÇÃO DE PONTOS INFLUENTES EM VARIÁVEIS CONTÍNUAS REGIONALIZADAS. Engenharia Agrícola. 36(1). 152–165. 1 indexed citations
20.
Bastiani, Fernanda De, et al.. (2014). Influence diagnostics in elliptical spatial linear models. Test. 24(2). 322–340. 41 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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