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The ratedistortion function for source coding with side information at the decoder
 IEEE Trans. Inform. Theory
, 1976
"... AbstractLet {(X,, Y,J}r = 1 be a sequence of independent drawings of a pair of dependent random variables X, Y. Let us say that X takes values in the finite set 6. It is desired to encode the sequence {X,} in blocks of length n into a binary stream*of rate R, which can in turn be decoded as a seque ..."
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Cited by 1048 (1 self)
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the quantity R*(d). defined as the infimum of rates R such that (with E> 0 arbitrarily small and with suitably large n) communication is possible in the above setting at an average distortion level (as defined above) not exceeding d + E. The main result is that R*(d) = inf[Z(X,Z) Z(Y,Z)], where
Exploration, normalization, and summaries of high density oligonucleotide array probe level data.
 Biostatistics,
, 2003
"... SUMMARY In this paper we report exploratory analyses of highdensity oligonucleotide array data from the Affymetrix GeneChip R system with the objective of improving upon currently used measures of gene expression. Our analyses make use of three data sets: a small experimental study consisting of f ..."
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Cited by 823 (33 self)
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intensities. We then examine the behavior of the P M and M M using spikein data and assess three commonly used summary measures: Affymetrix's (i) average difference (AvDiff) and (ii) MAS 5.0 signal, and (iii) the Li and Wong multiplicative modelbased expression index (MBEI). The exploratory data
Bayesian Model Averaging for Linear Regression Models
 Journal of the American Statistical Association
, 1997
"... We consider the problem of accounting for model uncertainty in linear regression models. Conditioning on a single selected model ignores model uncertainty, and thus leads to the underestimation of uncertainty when making inferences about quantities of interest. A Bayesian solution to this problem in ..."
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Cited by 310 (15 self)
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involves averaging over all possible models (i.e., combinations of predictors) when making inferences about quantities of
Model selection and accounting for model uncertainty in graphical models using Occam's window
, 1993
"... We consider the problem of model selection and accounting for model uncertainty in highdimensional contingency tables, motivated by expert system applications. The approach most used currently is a stepwise strategy guided by tests based on approximate asymptotic Pvalues leading to the selection o ..."
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Cited by 362 (47 self)
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Bayesian formalism which averages the posterior distributions of the quantity of interest under each of the models, weighted by their posterior model probabilities. Furthermore, this approach is optimal in the sense of maximising predictive ability. However, this has not been used in practice because
It’s Baaack! Japan’s Slump and the Return of the Liquidity Trap
 BPEA
, 1998
"... THE LIQUIDITY TRAPthat awkward condition in which monetary policy loses its grip because the nominal interest rate is essentially zero, in which the quantity of money becomes irrelevant because money and bonds are essentially perfect substitutesplayed a central role in the early years of macroecon ..."
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Cited by 332 (0 self)
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THE LIQUIDITY TRAPthat awkward condition in which monetary policy loses its grip because the nominal interest rate is essentially zero, in which the quantity of money becomes irrelevant because money and bonds are essentially perfect substitutesplayed a central role in the early years
Quantity
, 301
"... Please update your controlled set of documents with the following list of documents: ..."
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Please update your controlled set of documents with the following list of documents:
Quantity
, 2001
"... Please update your controlled set of documents with the following list of documents: ..."
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Please update your controlled set of documents with the following list of documents:
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