Jaime Puig-Pey

451 total citations
10 papers, 191 citations indexed

About

Jaime Puig-Pey is a scholar working on Statistics, Probability and Uncertainty, Computational Mechanics and Management Science and Operations Research. According to data from OpenAlex, Jaime Puig-Pey has authored 10 papers receiving a total of 191 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Statistics, Probability and Uncertainty, 3 papers in Computational Mechanics and 2 papers in Management Science and Operations Research. Recurrent topics in Jaime Puig-Pey's work include Advanced Statistical Process Monitoring (6 papers), Scientific Measurement and Uncertainty Evaluation (5 papers) and Advanced Numerical Analysis Techniques (3 papers). Jaime Puig-Pey is often cited by papers focused on Advanced Statistical Process Monitoring (6 papers), Scientific Measurement and Uncertainty Evaluation (5 papers) and Advanced Numerical Analysis Techniques (3 papers). Jaime Puig-Pey collaborates with scholars based in Spain, Japan and Peru. Jaime Puig-Pey's co-authors include Alberto Luceño, Akemi Gálvez and Andrés Iglesias and has published in prestigious journals such as Technometrics, Information Sciences and Applied Mathematical Modelling.

In The Last Decade

Jaime Puig-Pey

10 papers receiving 176 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jaime Puig-Pey Spain	8	75	69	34	32	31	10	191
Ky Vu France	4	23 0.3×	16 0.2×	8 0.2×	9 0.3×	9 0.3×	5	139
Luca Puggini United Kingdom	5	22 0.3×	5 0.1×	9 0.3×	20 0.6×	55 1.8×	7	157
Qiang Luo China	5	34 0.5×	27 0.4×	2 0.1×	78 2.4×	142 4.6×	17	217
Lars Mikelsons Germany	7	6 0.1×	10 0.1×	15 0.4×	31 1.0×	161 5.2×	37	211
Robin Hill Australia	9	13 0.2×	8 0.1×	14 0.4×	19 0.6×	87 2.8×	35	246
X. Nguyen France	8	68 0.9×	3 0.0×	83 2.4×	14 0.4×	24 0.8×	22	212
Marko Mihajlović Switzerland	5	2 0.0×	115 1.7×	139 4.1×	4 0.1×	46 1.5×	10	205
Igor D. Melo Brazil	9	9 0.1×	10 0.1×	6 0.2×	19 0.6×	157 5.1×	38	343
Jobert Ludlage Netherlands	7	26 0.3×	10 0.1×	3 0.1×	23 0.7×	246 7.9×	24	304
Giorgio Fasano Italy	8	4 0.1×	5 0.1×	11 0.3×	13 0.4×	16 0.5×	17	233

Countries citing papers authored by Jaime Puig-Pey

Since Specialization

Citations

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

Fields of papers citing papers by Jaime Puig-Pey

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jaime Puig-Pey. 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 Jaime Puig-Pey. The network helps show where Jaime Puig-Pey may publish in the future.

Co-authorship network of co-authors of Jaime Puig-Pey

This figure shows the co-authorship network connecting the top 25 collaborators of Jaime Puig-Pey. A scholar is included among the top collaborators of Jaime Puig-Pey 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 Jaime Puig-Pey. Jaime Puig-Pey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Gálvez, Akemi, Andrés Iglesias, & Jaime Puig-Pey. (2013). Computing parallel curves on parametric surfaces. Applied Mathematical Modelling. 38(9-10). 2398–2413. 21 indexed citations

2.

Gálvez, Akemi, Andrés Iglesias, & Jaime Puig-Pey. (2010). Iterative two-step genetic-algorithm-based method for efficient polynomial B-spline surface reconstruction. Information Sciences. 182(1). 56–76. 78 indexed citations

3.

Luceño, Alberto & Jaime Puig-Pey. (2006). The random intrinsic fast initial response of one-sided CUSUM charts. Journal of Applied Statistics. 33(2). 189–201. 4 indexed citations

4.

Puig-Pey, Jaime, et al.. (2005). Some applications of scalar and vector fields to geometric processing of surfaces. Computers & Graphics. 29(5). 719–725. 8 indexed citations

5.

Luceño, Alberto & Jaime Puig-Pey. (2002). Computing the Run Length Probability Distribution for CUSUM Charts. Journal of Quality Technology. 34(2). 209–215. 12 indexed citations

6.

Luceño, Alberto & Jaime Puig-Pey. (2002). An accurate algorithm to compute the run length probability distribution, and its convolutions, for a Cusum chart to control normal mean. Computational Statistics & Data Analysis. 38(3). 249–261. 10 indexed citations

7.

Luceño, Alberto & Jaime Puig-Pey. (2000). Evaluation of the Run-Length Probability Distribution for CUSUM Charts: Assessing Chart Performance. Technometrics. 42(4). 411–416. 36 indexed citations

8.

Luceño, Alberto & Jaime Puig-Pey. (2000). Evaluation of the Run-Length Probability Distribution for CUSUM Charts: Assessing Chart Performance. Technometrics. 42(4). 411–411. 9 indexed citations

9.

Puig-Pey, Jaime, et al.. (1999). Analytical expressions for the average adjustment interval and mean squared deviation for bounded adjustment schemes. Communications in Statistics - Simulation and Computation. 28(3). 623–635. 1 indexed citations

10.

Luceño, Alberto, et al.. (1996). Computing optimal adjustment schemes for the general tool-wear problem. Journal of Statistical Computation and Simulation. 54(1-3). 87–113. 12 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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