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The Calculus of M-Estimation in <i>R</i> with <b>geex</b>

Bradley Saul, Michael G. Hudgens

2020Journal of Statistical Software44 citationsDOIOpen Access PDF

Abstract

M-estimation, or estimating equation, methods are widely applicable for point estimation and asymptotic inference. In this paper, we present an R package that can find roots and compute the empirical sandwich variance estimator for any set of user-specified, unbiased estimating equations. Examples from the M-estimation primer by Stefanski and Boos (2002) demonstrate use of the software. The package also includes a framework for finite sample, heteroscedastic, and autocorrelation variance corrections, and a website with an extensive collection of tutorials.

Topics & Concepts

EstimatorHeteroscedasticityApplied mathematicsPoint estimationComputer scienceVariance (accounting)InferenceR packageEstimationMathematicsSet (abstract data type)StatisticsAutocorrelationProgramming languageArtificial intelligenceEconomicsManagementAccountingBusinessStatistical Methods and InferenceStatistical Methods and Bayesian InferenceAdvanced Causal Inference Techniques