Georgi N. Boshnakov

522 citations
34 papers · 256 indexed · h-index 9
Topics
Control Systems and Identification (6 papers)Financial Risk and Volatility Modeling (5 papers)Bayesian Methods and Mixture Models (4 papers)

In The Last Decade

Georgi N. Boshnakov

33 papers receiving 244 citations

Peers

Georgi N. Boshnakov
Comparison fields: 5 of 93
  • Economics and Econometrics 86
  • Artificial Intelligence 51
  • Statistics and Probability 45
  • Finance 31
  • Control and Systems Engineering 23
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Countries citing papers authored by Georgi N. Boshnakov

Since Specialization
Citations

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

Fields of papers citing papers by Georgi N. Boshnakov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Georgi N. Boshnakov. 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 Georgi N. Boshnakov. The network helps show where Georgi N. Boshnakov may publish in the future.

Co-authorship network of co-authors of Georgi N. Boshnakov

This figure shows the co-authorship network connecting the top 25 collaborators of Georgi N. Boshnakov. A scholar is included among the top collaborators of Georgi N. Boshnakov 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 Georgi N. Boshnakov. Georgi N. Boshnakov 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
#WorkIndexed citations
1
Simulation and Prediction with Seasonal ARIMA Models [R package sarima version 0.8.4]
1
2 4
3
R package Countr: Flexible Univariate Count Models Based on Renewal Processes
1
4
R package sarima: Simulation and Prediction with Seasonal ARIMA Models
1
5
StableEstim: Estimate the 4 parameters of stable law using different methods
1
6 8
7 12
8 8
9 53
10 5
11 2
12
{Non-Gaussian} Maximum Entropy Processes
1
13
Prediction with Mixture Autoregressive Models
1
14 0
15 3
16 3
17
On the asymptotic covariances of the multivariate serial correlations
2
18
A sufficient statistic and its application in ARMA estimation
1
19
Innovations, sufficient statistics and maximum likelihood in ARMA models
1
20
On the asymptotic distribution of the sample autocovariance and autocorrelation functions
3

About Georgi N. Boshnakov

Georgi N. Boshnakov is a scholar working on Statistics and Probability, Finance and Statistical and Nonlinear Physics, having authored 34 papers that have together received 256 indexed citations. Recurring topics across this work include Control Systems and Identification (6 papers), Financial Risk and Volatility Modeling (5 papers) and Bayesian Methods and Mixture Models (4 papers). The work is most often cited by research in Statistics and Probability (45 citations), Economics and Econometrics (86 citations) and Finance (31 citations). Georgi N. Boshnakov has collaborated with scholars based in United Kingdom, Bulgaria and France. Frequent co-authors include Ian G. McHale, Sophie Lambert‐Lacroix, Robert Zimmer and Rose Baker. Their work appears in journals such as Expert Systems with Applications, Journal of Statistical Software and International Journal of Forecasting.

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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