Zobrazeno 1 - 10
of 69
pro vyhledávání: '"Luís Montiel"'
We study a class of binary treatment choice problems with partial identification, through the lens of robust (multiple prior) Bayesian analysis. We use a convenient set of prior distributions to derive ex-ante and ex-post robust Bayes decision rules,
Externí odkaz:
http://arxiv.org/abs/2408.11621
We present a decision-theoretic justification for viewing the question of how to best choose where to experiment in order to optimize external validity as a k-median (clustering) problem, a popular problem in computer science and operations research.
Externí odkaz:
http://arxiv.org/abs/2408.09187
We consider impulse response inference in a locally misspecified vector autoregression (VAR) model. The conventional local projection (LP) confidence interval has correct coverage even when the misspecification is so large that it can be detected wit
Externí odkaz:
http://arxiv.org/abs/2405.09509
We apply classical statistical decision theory to a large class of treatment choice problems with partial identification, revealing important theoretical and practical challenges but also interesting research opportunities. The challenges are: In a g
Externí odkaz:
http://arxiv.org/abs/2312.17623
Autor:
Belkisyolé Alarcón de Noya, Cecilia Colmenares, Zoraida Díaz-Bello, Raiza Ruiz-Guevara, Karen Medina, Arturo Muñoz-Calderón, Luciano Mauriello, Elida Cabrera, Luís Montiel, Sandra Losada, Jetzi Martínez, Raúl Espinosa, Teresa Abate
Publikováno v:
Parasite Epidemiology and Control, Vol 1, Iss 2, Pp 188-198 (2016)
Oral transmission of Trypanosoma cruzi is a frequent cause of acute Chagas disease (ChD). In the present cross-sectional study, we report the epidemiological, clinical, serological and molecular outcomes of the second largest outbreak of oral ChD des
Externí odkaz:
https://doaj.org/article/948ad22edd544f5e9c0694da41697e63
We study the classical problem of predicting an outcome variable, $Y$, using a linear combination of a $d$-dimensional covariate vector, $\mathbf{X}$. We are interested in linear predictors whose coefficients solve: % \begin{align*} \inf_{\boldsymbol
Externí odkaz:
http://arxiv.org/abs/2211.07608
$\alpha$-posteriors and their variational approximations distort standard posterior inference by downweighting the likelihood and introducing variational approximation errors. We show that such distortions, if tuned appropriately, reduce the Kullback
Externí odkaz:
http://arxiv.org/abs/2104.08324
This paper shows that dropout training in Generalized Linear Models is the minimax solution of a two-player, zero-sum game where an adversarial nature corrupts a statistician's covariates using a multiplicative nonparametric errors-in-variables model
Externí odkaz:
http://arxiv.org/abs/2009.06111
Publikováno v:
Econometrica, July 2021, Volume 89, Issue 4, Pages 1789-1823
Applied macroeconomists often compute confidence intervals for impulse responses using local projections, i.e., direct linear regressions of future outcomes on current covariates. This paper proves that local projection inference robustly handles two
Externí odkaz:
http://arxiv.org/abs/2007.13888
Different agents need to make a prediction. They observe identical data, but have different models: they predict using different explanatory variables. We study which agent believes they have the best predictive ability -- as measured by the smallest
Externí odkaz:
http://arxiv.org/abs/1907.03809