Peter Spreij

1.1k total citations
79 papers, 584 citations indexed

About

Peter Spreij is a scholar working on Finance, Statistics and Probability and Artificial Intelligence. According to data from OpenAlex, Peter Spreij has authored 79 papers receiving a total of 584 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Finance, 33 papers in Statistics and Probability and 18 papers in Artificial Intelligence. Recurrent topics in Peter Spreij's work include Stochastic processes and financial applications (25 papers), Statistical Methods and Inference (19 papers) and Bayesian Methods and Mixture Models (15 papers). Peter Spreij is often cited by papers focused on Stochastic processes and financial applications (25 papers), Statistical Methods and Inference (19 papers) and Bayesian Methods and Mixture Models (15 papers). Peter Spreij collaborates with scholars based in Netherlands, Italy and Russia. Peter Spreij's co-authors include André Klein, Lorenzo Finesso, Bert van Es, André Lucas, Stefan Straetmans, Pieter Klaassen, Michel Mandjes, Matthijs van Veelen, Harry van Zanten and Gang Huang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Information Theory and Journal of Banking & Finance.

In The Last Decade

Peter Spreij

68 papers receiving 531 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter Spreij Netherlands 13 256 146 124 97 97 79 584
Denis Belomestny Germany 12 334 1.3× 126 0.9× 53 0.4× 130 1.3× 74 0.8× 79 510
P. Algoet United States 9 206 0.8× 90 0.6× 331 2.7× 167 1.7× 180 1.9× 14 805
Bernard Bercu France 15 300 1.2× 259 1.8× 129 1.0× 137 1.4× 56 0.6× 58 664
J. Michael Steele United States 9 102 0.4× 118 0.8× 81 0.7× 61 0.6× 52 0.5× 32 513
Łukasz Szpruch United Kingdom 12 411 1.6× 43 0.3× 65 0.5× 93 1.0× 81 0.8× 36 661
Noureddine El Karoui United States 14 203 0.8× 501 3.4× 253 2.0× 183 1.9× 132 1.4× 32 1.0k
Philippe Soulier France 14 517 2.0× 218 1.5× 131 1.1× 68 0.7× 310 3.2× 60 778
Karim M. Abadir United Kingdom 14 283 1.1× 236 1.6× 55 0.4× 67 0.7× 311 3.2× 60 791
Arup Bose India 15 224 0.9× 559 3.8× 123 1.0× 139 1.4× 169 1.7× 127 969
Miao Bai-qi China 12 122 0.5× 282 1.9× 109 0.9× 67 0.7× 93 1.0× 47 514

Countries citing papers authored by Peter Spreij

Since Specialization
Citations

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

Fields of papers citing papers by Peter Spreij

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter Spreij. 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 Peter Spreij. The network helps show where Peter Spreij may publish in the future.

Co-authorship network of co-authors of Peter Spreij

This figure shows the co-authorship network connecting the top 25 collaborators of Peter Spreij. A scholar is included among the top collaborators of Peter Spreij 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 Peter Spreij. Peter Spreij 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.
Belomestny, Denis, et al.. (2023). Weak solutions to gamma-driven stochastic differential equations. Indagationes Mathematicae. 34(4). 820–829.
2.
Huang, Gang, Michel Mandjes, & Peter Spreij. (2015). Large deviations for Markov-modulated diffusion processes with rapid switching. Stochastic Processes and their Applications. 126(6). 1785–1818. 11 indexed citations
3.
Finesso, Lorenzo & Peter Spreij. (2015). Factor analysis models via I-divergence optimization. Psychometrika. 81(3). 702–726. 1 indexed citations
4.
Spreij, Peter, et al.. (2014). Consistent non-parametric Bayesian estimation for a\n time-inhomogeneous Brownian motion. Springer Link (Chiba Institute of Technology). 3 indexed citations
5.
Klein, André & Peter Spreij. (2012). Transformed statistical distance measures and the fisher information matrix. Linear Algebra and its Applications. 437(2). 692–712. 2 indexed citations
6.
Spreij, Peter & Enno C.I. Veerman. (2010). The affine transform formula for affine diffusions with convex state space. arXiv (Cornell University). 1 indexed citations
7.
Es, Bert van & Peter Spreij. (2010). Estimation of a multivariate stochastic volatility density by kernel deconvolution. Journal of Multivariate Analysis. 102(3). 683–697. 3 indexed citations
8.
Klein, André & Peter Spreij. (2009). Tensor Sylvester matrices and the Fisher information matrix of VARMAX processes. Linear Algebra and its Applications. 432(8). 1975–1989. 3 indexed citations
9.
Klein, André & Peter Spreij. (2008). Matrix differential calculus applied to multiple stationary time series and an extended Whittle formula for information matrices. Linear Algebra and its Applications. 430(2-3). 674–691. 11 indexed citations
10.
Es, Bert van, Peter Spreij, & Harry van Zanten. (2005). Nonparametric volatility density estimation for discrete time models. Journal of nonparametric statistics. 17(2). 237–249. 13 indexed citations
11.
Klein, André & Peter Spreij. (2005). An explicit expression for the Fisher information matrix of a multiple time series process. Linear Algebra and its Applications. 417(1). 140–149. 7 indexed citations
12.
Klein, André & Peter Spreij. (2004). On the solution of Stein’s equation and Fisher’s information matrix of an ARMAX process. Linear Algebra and its Applications. 396. 1–34. 7 indexed citations
13.
Klein, André & Peter Spreij. (2001). On Stein's equation, Vandermonde matrices and Fisher's information matrix of time series processes. Part I: The autoregressive moving average process. Linear Algebra and its Applications. 329(1-3). 9–47. 14 indexed citations
14.
Klein, André & Peter Spreij. (1996). On Fisher's information matrix of an ARMAX process and Sylvester's resultant matrices. Linear Algebra and its Applications. 237-238. 579–590. 25 indexed citations
15.
Spreij, Peter, et al.. (1993). On correlation calculus for multivariate martingales. Stochastic Processes and their Applications. 46(2). 283–299. 4 indexed citations
16.
Spreij, Peter. (1991). Recursive approximate maximum likelihood estimation for a class of counting process models. Journal of Multivariate Analysis. 39(2). 236–245. 14 indexed citations
17.
Spreij, Peter, et al.. (1990). On second order optimality of regular projective estimators: Part I. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–20. 1 indexed citations
18.
Spreij, Peter. (1990). Self-exciting counting process systems with finite state space. Stochastic Processes and their Applications. 34(2). 275–295. 1 indexed citations
19.
Spreij, Peter, et al.. (1989). On SLLN for martingales with deterministic quadratic variation. Centrum Wiskunde & Informatica (CWI), the national research institute for mathematics and computer science in the Netherlands. 1–12. 3 indexed citations
20.
Spreij, Peter. (1989). Recursive approximate maximum likelihood estimation for a class of counting process models. Serie Research Memoranda. 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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