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Unifying the derivations for the Akaike and corrected Akaike information criteria

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  1. Roger Tovar-Falón & Guillermo Martínez-Flórez & Isaías Ceña-Tapia, 2023. "Some Extensions of the Asymmetric Exponentiated Bimodal Normal Model for Modeling Data with Positive Support," Mathematics, MDPI, vol. 11(7), pages 1-19, March.
  2. Craiu, Radu V. & Duchesne, Thierry, 2018. "A scalable and efficient covariate selection criterion for mixed effects regression models with unknown random effects structure," Computational Statistics & Data Analysis, Elsevier, vol. 117(C), pages 154-161.
  3. Yoonsuh Jung, 2018. "Multiple predicting K-fold cross-validation for model selection," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 30(1), pages 197-215, January.
  4. Guillermo Martínez-Flórez & Hector W. Gomez & Roger Tovar-Falón, 2021. "Modeling Proportion Data with Inflation by Using a Power-Skew-Normal/Logit Mixture Model," Mathematics, MDPI, vol. 9(16), pages 1-20, August.
  5. Sanku Dey & Emrah Altun & Devendra Kumar & Indranil Ghosh, 2023. "The Reflected-Shifted-Truncated Lomax Distribution: Associated Inference with Applications," Annals of Data Science, Springer, vol. 10(3), pages 805-828, June.
  6. Liu, Xiaomei & Li, Sihan & Gao, Meina, 2024. "A discrete time-varying grey Fourier model with fractional order terms for electricity consumption forecast," Energy, Elsevier, vol. 296(C).
  7. Bengtsson, Thomas & Cavanaugh, Joseph E., 2006. "An improved Akaike information criterion for state-space model selection," Computational Statistics & Data Analysis, Elsevier, vol. 50(10), pages 2635-2654, June.
  8. Cavanaugh, Joseph E., 1999. "A large-sample model selection criterion based on Kullback's symmetric divergence," Statistics & Probability Letters, Elsevier, vol. 42(4), pages 333-343, May.
  9. Massimo Guidolin & Manuela Pedio, 2020. "Distilling Large Information Sets to Forecast Commodity Returns: Automatic Variable Selection or HiddenMarkov Models?," BAFFI CAREFIN Working Papers 20140, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
  10. Fábio Bayer & Francisco Cribari-Neto, 2015. "Bootstrap-based model selection criteria for beta regressions," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(4), pages 776-795, December.
  11. An Hoai Duong & Ernoiz Antriyandarti, 2023. "The Willingness to get Vaccinated Against SARS-CoV-2 Virus among Southeast Asian Countries: Does the Vaccine Brand Matter?," Applied Research in Quality of Life, Springer;International Society for Quality-of-Life Studies, vol. 18(2), pages 765-793, April.
  12. Sobieralski, Joseph B., 2013. "The optimal aviation gasoline tax for U.S. general aviation," Transport Policy, Elsevier, vol. 29(C), pages 186-191.
  13. Xu, Danli & Wang, Yong, 2023. "Density estimation for spherical data using nonparametric mixtures," Computational Statistics & Data Analysis, Elsevier, vol. 182(C).
  14. Carlos A. Medel, 2015. "Probabilidad Clásica de Sobreajuste con Criterios de Información: Estimaciones con Series Macroeconómicas Chilenas," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 30(1), pages 57-72, Abril.
  15. Qu, Zhongjun & Perron, Pierre, 2007. "A Modified Information Criterion For Cointegration Tests Based On A Var Approximation," Econometric Theory, Cambridge University Press, vol. 23(4), pages 638-685, August.
  16. Shahrestani, Parnia & Rafei, Meysam, 2020. "The impact of oil price shocks on Tehran Stock Exchange returns: Application of the Markov switching vector autoregressive models," Resources Policy, Elsevier, vol. 65(C).
  17. You, Kisung & Suh, Changhee, 2022. "Parameter estimation and model-based clustering with spherical normal distribution on the unit hypersphere," Computational Statistics & Data Analysis, Elsevier, vol. 171(C).
  18. Wang, Xiaolei & Xie, Naiming & Yang, Lu, 2022. "A flexible grey Fourier model based on integral matching for forecasting seasonal PM2.5 time series," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).
  19. Guillermo Martínez-Flórez & David Elal-Olivero & Carlos Barrera-Causil, 2021. "Extended Generalized Sinh-Normal Distribution," Mathematics, MDPI, vol. 9(21), pages 1-24, November.
  20. Farid Shirazi & Nick Hajli, 2021. "IT-Enabled Sustainable Innovation and the Global Digital Divides," Sustainability, MDPI, vol. 13(17), pages 1-24, August.
  21. Jed Armstrong & Özer Karagedikli, 2017. "The role of non-participants in labour market dynamics," Reserve Bank of New Zealand Analytical Notes series AN2017/01, Reserve Bank of New Zealand.
  22. Giuseppe Brandi & Ruggero Gramatica & Tiziana Di Matteo, 2019. "Unveil stock correlation via a new tensor-based decomposition method," Papers 1911.06126, arXiv.org, revised Apr 2020.
  23. Adam J. Wyness & David M. Paterson & James E. V. Rimmer & Emma C. Defew & Marc I. Stutter & Lisa M. Avery, 2019. "Assessing Risk of E. coli Resuspension from Intertidal Estuarine Sediments: Implications for Water Quality," IJERPH, MDPI, vol. 16(18), pages 1-13, September.
  24. Hojin Moon & Hyun‐Joo Kim & James J. Chen & Ralph L. Kodell, 2005. "Model Averaging Using the Kullback Information Criterion in Estimating Effective Doses for Microbial Infection and Illness," Risk Analysis, John Wiley & Sons, vol. 25(5), pages 1147-1159, October.
  25. Ng, Serena, 2013. "Variable Selection in Predictive Regressions," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 752-789, Elsevier.
  26. Melisso Boschi & Alessandro Girardi & Marco Ventura, 2022. "The relative effectiveness of EU national and supranational fiscal rules," Working Papers in Public Economics 222, University of Rome La Sapienza, Department of Economics and Law.
  27. Haoyang Lu & Li Yi & Hang Zhang, 2019. "Autistic traits influence the strategic diversity of information sampling: Insights from two-stage decision models," PLOS Computational Biology, Public Library of Science, vol. 15(12), pages 1-29, December.
  28. Detering, Nils & Packham, Natalie, 2018. "Model risk of contingent claims," IRTG 1792 Discussion Papers 2018-036, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
  29. Thapa, Nischal, 2020. "Being cognizant of the amount of information: Curvilinear relationship between total-information and funding-success of crowdfunding campaigns," Journal of Business Venturing Insights, Elsevier, vol. 14(C).
  30. Hafidi, B. & Mkhadri, A., 2006. "A corrected Akaike criterion based on Kullback's symmetric divergence: applications in time series, multiple and multivariate regression," Computational Statistics & Data Analysis, Elsevier, vol. 50(6), pages 1524-1550, March.
  31. Fabian Paul & Thomas R Weikl, 2016. "How to Distinguish Conformational Selection and Induced Fit Based on Chemical Relaxation Rates," PLOS Computational Biology, Public Library of Science, vol. 12(9), pages 1-17, September.
  32. Zed Zulkafli & Farrah Melissa Muharam & Nurfarhana Raffar & Amirparsa Jajarmizadeh & Mukhtar Jibril Abdi & Balqis Mohamed Rehan & Khairudin Nurulhuda, 2021. "Contrasting Influences of Seasonal and Intra-Seasonal Hydroclimatic Variabilities on the Irrigated Rice Paddies of Northern Peninsular Malaysia for Weather Index Insurance Design," Sustainability, MDPI, vol. 13(9), pages 1-23, May.
  33. Nitithumbundit, Thanakorn & Chan, Jennifer S.K., 2022. "Covid-19 impact on Cryptocurrencies market using Multivariate Time Series Models," The Quarterly Review of Economics and Finance, Elsevier, vol. 86(C), pages 365-375.
  34. Thi Mai Hoa Ha & Derrick Yong & Elizabeth Mei Yin Lee & Prathab Kumar & Yuan Kun Lee & Weibiao Zhou, 2017. "Activation and inactivation of Bacillus pumilus spores by kiloelectron volt X-ray irradiation," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-15, May.
  35. Marhuenda, Yolanda & Morales, Domingo & del Carmen Pardo, María, 2014. "Information criteria for Fay–Herriot model selection," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 268-280.
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