Statistical Models

By David M. Blei. 2014

622 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

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Citations in the corpus

Visualizing the effects of predictor variables in black box supervised learning models (2016, background): “Conditioning plots (coplots) (Chambers and Hastie, 1992; Cleveland, 1993), conditional response plots (Cook, 1995) and individual conditional expectation plots (Goldstein et al., 2015) plot quantities like f.xj, x\j/ against xj for a collection of discrete values of x\j (conditional response and…”
The scaling of human interactions with city size (2012, methodology): “We first calculated for each interaction indicator, each model i and individual city c the maximum value of the log-likelihood function lnLi,c [32].”
Testing environmental and genetic effects in the presence of spatial autocorrelation (2014, methodology): “…correlated process; however, all inferences are conditional on the realized values of the design matrix X, that is the set of xis for all positions (Davison 2003, p. 648; Cox 2006, p. 46), and therefore the GLMM analysis makes no assumption whether the elements of X are conceived as correlated…”
Information geometry and sufficient statistics (2012, background): “In [27] and [28], Lˆe proved the following variant of the locality condition, which has been asked by Lauritzen [26] and Amari-Nagaoka [4].”
Spatial regression models for extreme precipitation in Belgium (2012, methodology): “A solution to account for the dependence is ignoring the dependence initially, thus working with MLE under misspecification, and then making adjustments to estimates of parameter uncertainty [Davison, 2003; R. L. Smith, unpublished manuscript, 1990b].”
Foundations of Linear and Generalized Linear Models (2015, background): “Davison (2003, Section 5.2), Morris (1982, 1983a), and Pace and Salvan (1997, Chapters 5 and 6) surveyed properties of exponential family models and their extensions. 4.2 GLMs: For more on GLMs, see Davison (2003), Fahrmeir and Tutz (2001), Faraway (2006), Firth (1991), Hastie and Pregibon (1991), L”
Likelihood estimators for multivariate extremes (2014, methodology): “The simulated data are positive, with a positive mass at zero, and heavytailed, which are common features of rainfall data for example (Huser and Davison, 2014). The presence of the point mass at zero could be problematic for non-censored estimators. The distribution (31) is known to be in the max-d”
Simple rules to guide expert classifications (2020, background): “As is common, the categories of an ordinal variable are represented as sequential integers, with our complex models fitting orthogonal polynomials to these integer values (Chambers et al., 1992).”
The misuse of the Vuong test for non-nested models to test for zero-inflation (2015, neutral): “Simple definitions of nested model include that of Davison (2003): “Two models are said to be nested if one reduces to the other when certain parameters are fixed.””
Visualizing Fit and Lack of Fit in Complex Regression Models with Predictor Effect Plots and Partial Residuals (2018, methodology): “If we assume that the value of this difference has a symmetric distribution about zero, then, from Cook (1993, Lemma 2.1), the unadjusted partial residual plot (7) visualizes t(xf ) with extra variation.”