The behavior of maximum likelihood estimates under nonstandard conditions

By Philippe Huber. 1967

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Citations in the corpus

The Econometrics of Randomized Experiments (2016, methodology): “Athey and Imbens (2016) develop a method for exploring heterogeneity in treatment effects without having to prespecify the form of the heterogeneity, and without having to worry about multiple testing.”
Robust Estimators in High Dimensions without the Computational Intractability (2016, neutral): “Keywords-unsupervised learning, statistical learning, density estimation robust algorithm I. INTRODUCTION”
Flow-GAN: Combining Maximum Likelihood and Adversarial Learning in Generative Models (2017, background): “From a statistical perspective, maximum likelihood estimators are statistically efficient asymptotically (under some conditions) and hence minimizing the KL divergence is a natural objective for many prescribed models (Huber 1967).”
Invariances and Diversities in the Patterns of Industrial Evolution: Some Evidence from Italian Manufacturing Industries (2007, background): “among many others Hart and Prais (1956), Simon and Bonini (1958), Hymer and Pashigian (1962), Mansfield (1962), Bottazzi and Secchi (2003)) on different databases.”
Understanding Robust Corrections in Structural Equation Modeling (2014, background): “They are sometimes known as heterogeneous standard errors in the regression literature, and as “sandwich” standard errors in statistical and econometric literature (Hardin, 2003; Huber, 1967; White, 1980, 1982).”
Financing Frictions and the Substitution between Internal and External Funds (2010, unknown): “This testing approach, which follows from Shyam-Sunder and Myers (1999), implicitly assumes that observed investment is equal to desired investment even when the firm faces capital market frictions. In contrast to this, we argue that the endogeneity of financing and investment decisions influence th”
The Analysis of Household Surveys (Reissue Edition with a New Preface): A Microeconometric Approach to Development Policy (2018, methodology): “This formula, which comes originally from Eicker (1967) and Huber (1967), was introduced into econometrics by White (1980).”
How Does Workplace Helping Behavior Step Up or Slack Off? Integrating Enrichment-Based and Depletion-Based Perspectives (2018, methodology): “…sandwich estimator to account for the nonindependence of observations due to cluster sampling at the department level in order to provide robust estimation of the standard errors in our model (Huber, 1967; Y. Liu, Wang, Chang, Shi, & Zhou, 2015; Muthén & Muthén, 2012; Rogers, 1993; White, 1980).”
Decomposition of differences in distribution using quantile regression (2005, methodology): “Using Powell’s (1984 and 1986) and Huber’s (1967) results, the derivatives operators in 1 R and 2 R can be brought outside the”
"A Hand upon the Throat of the Nation": Economic Sanctions and State Repression, 1976-2001 (2008, methodology): “Ordered probit models use Huber (1967) and White (1980) robust standard errors clustered on the country to control for heteroskedasticity.”
Semiparametric Counterfactual Density Estimation (2021, methodology): “…assumed correct but instead only used for defining approximations, has been used widely throughout statistics [Beran, 1977, Buja et al., 2019a,b, Huber, 1967, Rakhlin et al., 2017, Rinaldo and Wasserman, 2010, Tsybakov, 2003, Wasserman, 2006, White, 1982, 1996] as well as in causal inference…”
An efficient and robust statistical modeling approach to discover differentially expressed genes using genomic expression profiles. (2001, methodology): “Because we do not impose distributional assumptions about residuals, the third step is to use the weighted least square (Huber 1967) to estimate genespecific parameters (a j , b j ) in the model (equation 1).”