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Information Theory and an Extension of the Maximum Likelihood Principle
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A Mathematical Theory of Communication
Shannon, C. E. (1948) · Bell System Technical Journal · doi:10.1002/j.1538-7305.1948.tb01338.x · Cited by 88,486
Research works printed but not linked: 27
- Akaike, H., Fitting autoregressive models for prediction. Ann. Inst. Statist. Math. 21 (1969) 243–217. · DOI
- Akaike., H., Statistical predictor identification. Ann. Inst. Statist. Math. 22 (1970) 203–217. · DOI · Paper page
- Akaike, H., On a semi-automatic power spectrum estimation procedure. Proc. 3rd Hawaii International Conference on System Sciences, 1970, 974–977.
- Akaike, H., On a decision procedure for system identification, Preprints, IFAC Kyoto Symposium on System Engineering Approach to Computer Control. 1970, 486–490.
- Akaike, H., Autoregressive model fitting for control. Ann. Inst. Statist. Math. 23 (1971) 163–180. · DOI
- Akaike, H., Determination of the number of factors by an extended maximum likelihood principle. Research Memo. 44, Inst. Statist. Math. March, 1971.
- Bartlett, M. S., The statistical approach to the analysis of time-series. Symposium on Information Theory (mimeographed Proceedings), Ministry of Supply, London, 1950, 81–101.
- Billingsley, P., Statistical Inference for Markov Processes. Univ. Chicago Press, Chicago 1961.
- Blackwell, D., Equivalent comparisons of experiments. Ann. Math. Statist. 24 (1953) 265–272. · DOI
- Campbell, L.L., Equivalence of Gauss’s principle and minimum discrimination information estimation of probabilities. Ann. Math. Statist. 41 (1970) 10111015. · DOI
- Fisher, R.A., Theory of statistical estimation. Proc. Camb. Phil. Soc. 22 (1925) 700–725, Contributions to Mathematical Statistics John Wiley & Sons, New York, 1950, paper 11. · DOI
- Good, I.J. Maximum entropy for hypothesis formulation, especially for multidimensional contingency tables. Ann. Math. Statist. 34 (1963) 911–934. · DOI
- Gorman, J.W. and Toman, R.J., Selection of variables for fitting equations to data. Technometrics 8 (1966) 27–51. · DOI
- Jenkins, G.M. and Watts, D.G., Spectral Analysis and Its Applications. Holden Day, San Francisco, 1968.
- Kullback, S. and Leibler, R.A., On information and sufficiency. Ann. Math Statist. 22 (1951) 79–86. · DOI · Paper page
- Kullback, S., Information Theory and Statistics. John Wiley & Sons, New York 1959.
- Le Cam, L., On some asymptotic properties of maximum likelihood estimates and related Bayes estimates. Univ. Calif. Publ. in Stat. 1 (1953) 277–330.
- Lehmann, E.L., Testing Statistical Hypotheses. John Wiley & Sons, New York 1969.
- Otomo, T., Nakagawa, T. and Akaike, H. Statistical approach to computer control of cement rotary kilns. 1971. Automatica 8 (1972) 35–48. · DOI
- Rényi, A., Statistics and information theory. Studia Sci. Math. Hung. 2 (1967) 249–256.
- Savage, L.J., The Foundations of Statistics. John Wiley & Sons, New York 1954.
- Wald, A., Tests of statistical hypotheses concerning several parameters when the number of observations is large. Trans. Am. Math. Soc. 54 (1943) 426–482. · DOI
- Wald, A., Note on the consistency of the maximum likelihood estimate. Ann Math. Statist. 20 (1949) 595–601. · DOI
- Wald, A., Statistical Decision Functions. John Wiley & Sons, New York 1950.
- Whittle, P., The statistical analysis of seiche record. J. Marine Res. 13 (1954) 76–100.
- Whittle, P., Prediction and Regulation. English Univ. Press, London 1963.
- Wiener, N., Cybernetics. John Wiley & Sons, New York, 1948.
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Spiegelhalter, D. J., Best, N. G., Carlin, B. P., & Van Der Linde, A. (2002) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00353 · Cited by 151
Kass, R. E., & Raftery, A. E. (1995) · Journal of the American Statistical Association · doi:10.1080/01621459.1995.10476572 · Cited by 12,558
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Bozdogan, H. (1987) · Psychometrika · doi:10.1007/bf02294361 · Cited by 4,468
Hoeting, J. A., Madigan, D., Raftery, A. E., & Volinsky, C. T. (1999) · Statistical Science · doi:10.1214/ss/1009212519 · Cited by 4,118
Burnham, K. P., Anderson, D. R., & Huyvaert, K. P. (2011) · Behavioral Ecology and Sociobiology · doi:10.1007/s00265-010-1029-6 · Cited by 4,104
Posada, D., & Buckley, T. R. (2004) · Systematic Biology · doi:10.1080/10635150490522304 · Cited by 3,927
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Arlot, S., & Celisse, A. (2010) · Statistics Surveys · doi:10.1214/09-ss054 · Cited by 3,522
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Villemagne, V. L., Burnham, S., Bourgeat, P., Brown, B., Ellis, K. A., Salvado, O., Szoeke, C., Macaulay, S. L., Martins, R., Maruff, P., et al. (2013) · The Lancet Neurology · doi:10.1016/s1474-4422(13)70044-9 · Cited by 2,279
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Anderson, H. R., Bremner, S. A., Atkinson, R. W., Harrison, R. M., & Walters, S. (2001) · Occupational and Environmental Medicine · doi:10.1136/oem.58.8.504 · Cited by 230
Kim, S., Imoto, S., & Miyano, S. (2004) · Biosystems · doi:10.1016/j.biosystems.2004.03.004 · Cited by 224
Hauser, T. U., Iannaccone, R., Walitza, S., Brandeis, D., & Brem, S. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.09.018 · Cited by 203
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Glover, S., & Dixon, P. (2004) · Psychonomic Bulletin & Review · doi:10.3758/bf03196706 · Cited by 218
Ladpli, P., Kopsaftopoulos, F., & Chang, F.-K. (2018) · Journal of Power Sources · doi:10.1016/j.jpowsour.2018.02.056 · Cited by 214
Link, V. M., Duttke, S. H., Chun, H. B., Holtman, I. R., Westin, E., Hoeksema, M. A., Abe, Y., Skola, D., Romanoski, C. E., Tao, J., et al. (2018) · Cell · doi:10.1016/j.cell.2018.04.018 · Cited by 182
Trust transfer in the continued usage of public e-services
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Ly, L. P., & Handelsman, D. J. (2005) · European Journal of Endocrinology · doi:10.1530/eje.1.01844 · Cited by 180
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Czamara, D., Eraslan, G., Page, C. M., Lahti, J., Lahti-Pulkkinen, M., Hämäläinen, E., Kajantie, E., Laivuori, H., Villa, P. M., Reynolds, R. M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10461-0 · Cited by 143
Daniels, R. D., Bertke, S., Dahm, M. M., Yiin, J. H., Kubale, T. L., Hales, T. R., Baris, D., Zahm, S. H., Beaumont, J. J., Waters, K. M., et al. (2015) · Occupational and Environmental Medicine · doi:10.1136/oemed-2014-102671 · Cited by 140
Pearson, M. R., Lawless, A. K., Brown, D. B., & Bravo, A. J. (2015) · Personality and Individual Differences · doi:10.1016/j.paid.2014.11.009 · Cited by 140
Lai, Z., & Nagarajaiah, S. (2019) · Mechanical Systems and Signal Processing · doi:10.1016/j.ymssp.2018.08.033 · Cited by 134
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Metadata
- Authors
- Akaike, H.
- Venue
- Springer Series in Statistics
- Publisher
- Springer New York
- Published
- 1998
- Pages
- 199-213
- ISSN
- 0172-7397 (ISSN-L)
- OpenAlex
- W2058815839
- Cited by
- 17,781
- References
- 1
- FWCI
- 561.65
- Type
- book chapter
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.