Assessing the distinguishability of models and the informativeness of data

[1]  H. Jeffreys,et al.  Theory of probability , 1896 .

[2]  Edward K. Strong,et al.  The effect of time-interval upon recognition memory. , 1913 .

[3]  H. E. Burtt,et al.  The curve of forgetting for advertising material. , 1925 .

[4]  W. C. F. Krueger.  The effect of overlearning on retention. , 1929 .

[5]  W. Estes.  The problem of inference from curves based on group data. , 1956, Psychological bulletin.

[6]  Estes Wk.  The problem of inference from curves based on group data. , 1956 .

[7]  L. R. Peterson,et al.  Short-term retention of individual verbal items. , 1959, Journal of experimental psychology.

[8]  B. Murdock,et al.  The retention of individual items. , 1961, Journal of experimental psychology.

[9]  A. Bregman.  Forgetting curves with semantic, phonetic, graphic, and contiguity cues. , 1968 .

[10]  Wayne A. Wickelgren,et al.  Sparing of short-term memory in an amnesic patient: Implications for strength theory of memory , 1968 .

[11]  Wayne A. Wickelgren,et al.  Trace resistance and the decay of long-term memory. , 1972 .

[12]  H. P. Bahrick,et al.  Fifty years of memory for names and faces: A cross-sectional approach. , 1975 .

[13]  G. Kimble,et al.  Recognition memory for words and pictures at short and long retention intervals , 1976, Memory & cognition.

[14]  G. Box.  Science and Statistics , 1976 .

[15]  D. Massaro,et al.  Integration of featural information in speech perception. , 1978, Psychological review.

[16]  N. Anderson.  Foundations of information integration theory , 1981 .

[17]  C. Thompson,et al.  Memory for unique personal events: The roommate study , 1982, Memory & cognition.

[18]  W. Runquist,et al.  Some effects of remembering on forgetting , 1983, Memory & cognition.

[19]  James L. McClelland,et al.  The TRACE model of speech perception , 1986, Cognitive Psychology.

[20]  R. Nosofsky.  Attention, similarity, and the identification-categorization relationship. , 1986, Journal of experimental psychology. General.

[21]  R. Shepard,et al.  Toward a universal law of generalization for psychological science. , 1987, Science.

[22]  R. Knight,et al.  The effect of intellectual deterioration on retention deficits in amnesic alcoholics. , 1988, Journal of abnormal psychology.

[23]  Steven A. Sloman,et al.  Forgetting in primed fragment completion. , 1988 .

[24]  Colin M. Macleod,et al.  Forgotten but not gone: savings for pictures and words in long-term memory. , 1988, Journal of experimental psychology. Learning, memory, and cognition.

[25]  Colin M. Macleod,et al.  Forgotten but not gone: savings for pictures and words in long-term memory. , 1988, Journal of experimental psychology. Learning, memory, and cognition.

[26]  L. Squire,et al.  On the course of forgetting in very long-term memory. , 1989, Journal of experimental psychology. Learning, memory, and cognition.

[27]  J. Wixted,et al.  On the Form of Forgetting , 1991 .

[28]  John R. Anderson,et al.  Reflections of the Environment in Memory Form of the Memory Functions , 2022 .

[29]  M. Conway,et al.  On the Very Long-Term Retention of Knowledge Acquired Through Formal Education: Twelve Years of Cognitive Psychology , 1991 .

[30]  M. Conway,et al.  VERY LONG TERM RETENTION OF KNOWLEDGE , 1992 .

[31]  R M Nosofsky,et al.  Similarity-scaling studies of dot-pattern classification and recognition. , 1992, Journal of experimental psychology. General.

[32]  M. Murray,et al.  Differential Geometry and Statistics , 1993 .

[33]  Christian P. Robert,et al.  The Bayesian choice , 1994 .

[34]  Gregory Ashby,et al.  On the Dangers of Averaging Across Subjects When Using Multidimensional Scaling or the Similarity-Choice Model , 1994 .

[35]  A. Raftery.  Bayesian Model Selection in Social Research , 1995 .

[36]  D. Rubin,et al.  One Hundred Years of Forgetting : A Quantitative Description of Retention , 1996 .

[37]  L. Wasserman,et al.  The Selection of Prior Distributions by Formal Rules , 1996 .

[38]  Jorma Rissanen,et al.  Fisher information and stochastic complexity , 1996, IEEE Trans. Inf. Theory.

[39]  L. Wasserman,et al.  Computing Bayes Factors by Combining Simulation and Asymptotic Approximations , 1997 .

[40]  Sylvia Richardson,et al.  Markov Chain Monte Carlo in Practice , 1997 .

[41]  I. J. Myung,et al.  Applying Occam’s razor in modeling cognition: A Bayesian approach , 1997 .

[42]  Vijay Balasubramanian,et al.  Statistical Inference, Occam's Razor, and Statistical Mechanics on the Space of Probability Distributions , 1996, Neural Computation.

[43]  J. Wixted,et al.  Genuine power curves in forgetting: A quantitative analysis of individual subject forgetting functions , 1997, Memory & cognition.

[44]  John Geweke,et al.  Federal Reserve Bank of Minneapolis Research Department Staff Report 249 Using Simulation Methods for Bayesian Econometric Models: Inference, Development, and Communication , 2022 .

[45]  James O. Berger,et al.  Simulation Methods for Model Criticism and Robustness Analysis , 1998 .

[46]  D. Rubin,et al.  The Precise Time Course of Retention , 1999 .

[47]  P. Gr,et al.  Model Selection Based on Minimum Description Length , 1999 .

[48]  The Memory Laws of Jost , 1999 .

[49]  D Norris,et al.  Merging information in speech recognition: Feedback is never necessary , 2000, Behavioral and Brain Sciences.

[50]  Anne Cutler,et al.  Merging phonetic and lexical information in phonetic decision-making , 2000 .

[51]  I. J. Myung,et al.  Toward an explanation of the power law artifact: Insights from response surface analysis , 2000, Memory & cognition.

[52]  I. J. Myung,et al.  Counting probability distributions: Differential geometry and model selection , 2000, Proc. Natl. Acad. Sci. USA.

[53]  Grünwald,et al.  Model Selection Based on Minimum Description Length. , 2000, Journal of mathematical psychology.

[54]  Jorma Rissanen,et al.  Strong optimality of the normalized ML models as universal codes and information in data , 2001, IEEE Trans. Inf. Theory.

[55]  D K Smith,et al.  Numerical Optimization , 2001, J. Oper. Res. Soc..

[56]  Comparing prototype-based and exemplar-based accounts of category learning and attentional allocation. , 2002 .

[57]  Jeff Gill,et al.  Bayesian Methods : A Social and Behavioral Sciences Approach , 2002 .

[58]  S. Sikström.  Forgetting curves: implications for connectionist models , 2002, Cognitive Psychology.

[59]  I. J. Myung,et al.  Toward a method of selecting among computational models of cognition. , 2002, Psychological review.

[60]  Mark A. Pitt,et al.  An MCMC-Based Method of Comparing Connectionist Models in Cognitive Science , 2003, NIPS.

[61]  Mark A. Pitt,et al.  Global Model Analysis by Landscaping , 2003 .

[62]  Yong Su.  3 Minimum Description Length and Cognitive Modeling , 2003 .

[63]  M. Lee,et al.  Avoiding the dangers of averaging across subjects when using multidimensional scaling , 2003 .

[64]  I. J. Myung,et al.  Tutorial on maximum likelihood estimation , 2003 .

[65]  Woojae Kim,et al.  Flexibility versus generalizability in model selection , 2003, Psychonomic bulletin & review.

[66]  A. Heathcote,et al.  Averaging learning curves across and within participants , 2003, Behavior research methods, instruments, & computers : a journal of the Psychonomic Society, Inc.

[67]  Joshua B. Tenenbaum,et al.  Inferring causal networks from observations and interventions , 2003, Cogn. Sci..

[68]  D. Kirsh,et al.  Proceedings of the 25th annual conference of the Cognitive Science Society , 2003 .

[69]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[70]  Daniel J. Navarro,et al.  A Note on the Applied Use of MDL Approximations , 2004, Neural Computation.

[71]  Roger Ratcliff,et al.  Assessing model mimicry using the parametric bootstrap , 2004 .

[72]  Philip L. Smith,et al.  A comparison of sequential sampling models for two-choice reaction time. , 2004, Psychological review.

[73]  Mark A. Pitt,et al.  Advances in Minimum Description Length: Theory and Applications , 2005 .