Esther López-Vizcaíno
Statistics and Probability · 2013–2015
A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 3 researchers here, as inferred from the citation graph.
Subfields
- Statistics and Probability — 10 citations into it
- Economics and Econometrics — 9 citations into it; #12,182 of 23,481 by trust here, #20,008 by citations
- Management Science and Operations Research — 9 citations into it; #6,035 of 11,946 by trust here, #9,383 by citations
- Sociology and Political Science — 5 citations into it
Whom Esther López-Vizcaíno trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- A. Saei
- Danny Pfeffermann
- Jiming Jiang
- Isabel Molina
- M. José Lombardía
- Partha Lahiri
- Peter Hall
- Florin Vaida
- R. Chambers
- Gauri Sankar Datta
Who trusts Esther López-Vizcaíno overall
Papers from Esther López-Vizcaíno's perspective
Ordered by how strongly the researchers Esther López-Vizcaíno trusts endorse each paper. Same corpus, a different order for every researcher.
- Mixed model prediction and small area estimation
- On parametric bootstrap methods for small area prediction
- On measures of uncertainty of empirical Bayes small-area estimators
- Bootstrap Approximation to Prediction MSE for State–Space Models with Estimated Parameters
- Empirical Bayes estimation of median income of four-person families by state using time series and cross-sectional data
- New important developments in small area estimation
- Conditional Akaike information for mixed-effects models
- A unified jackknife theory for empirical best prediction with M-estimation
- Bootstrap mean squared error of a small-area EBLUP
- A UNIFIED MEASURE OF UNCERTAINTY OF ESTIMATED BEST LINEAR UNBIASED PREDICTORS IN SMALL AREA ESTIMATION PROBLEMS
Their papers
- Multinomial-based small area estimation of labour force indicators* (2013) — 64 citations
- Small area estimation of labour force indicators under a multinomial model with correlated time and area effects (2015) — 65 citations