| Education and entrepreneurial choice: An instrumental variables analysis JH Block, L Hoogerheide, R Thurik International Small Business Journal 31 (1), 23-33, 2013 | 237 | 2013 |
| On the shape of posterior densities and credible sets in instrumental variable regression models with reduced rank: an application of flexible sampling methods using neural … LF Hoogerheide, JF Kaashoek, HK Van Dijk Journal of Econometrics 139 (1), 154-180, 2007 | 125 | 2007 |
| Family background variables as instruments for education in income regressions: A Bayesian analysis L Hoogerheide, JH Block, R Thurik Economics of Education Review 31 (5), 515-523, 2012 | 115 | 2012 |
| Bayesian forecasting of value at risk and expected shortfall using adaptive importance sampling L Hoogerheide, HK van Dijk International Journal of Forecasting 26 (2), 231-247, 2010 | 103 | 2010 |
| Bayesian estimation of the garch (1, 1) model with student-t innovations D Ardia, LF Hoogerheide The R Journal 2 (2), 41-47, 2010 | 89 | 2010 |
| Natural conjugate priors for the instrumental variables regression model applied to the Angrist–Krueger data L Hoogerheide, F Kleibergen, HK van Dijk Journal of Econometrics 138 (1), 63-103, 2007 | 75 | 2007 |
| Forecast accuracy and economic gains from Bayesian model averaging using time‐varying weights L Hoogerheide, R Kleijn, F Ravazzolo, HK Van Dijk, M Verbeek Journal of Forecasting 29 (1‐2), 251-269, 2010 | 69 | 2010 |
| A class of adaptive importance sampling weighted EM algorithms for efficient and robust posterior and predictive simulation L Hoogerheide, A Opschoor, HK Van Dijk Journal of Econometrics 171 (2), 101-120, 2012 | 66 | 2012 |
| GARCH models for daily stock returns: Impact of estimation frequency on Value-at-Risk and Expected Shortfall forecasts D Ardia, LF Hoogerheide Economics Letters 123 (2), 187-190, 2014 | 65 | 2014 |
| Genome-wide analysis of macrosatellite repeat copy number variation in worldwide populations: evidence for differences and commonalities in size distributions and size restrictions M Schaap, RJLF Lemmers, R Maassen, PJ van der Vliet, LF Hoogerheide, ... BMC genomics 14, 1-12, 2013 | 57 | 2013 |
| A comparative study of Monte Carlo methods for efficient evaluation of marginal likelihood D Ardia, N Baştürk, L Hoogerheide, HK Van Dijk Computational Statistics & Data Analysis 56 (11), 3398-3414, 2012 | 55 | 2012 |
| Adaptive mixture of Student-t distributions as a flexible candidate distribution for efficient simulation: The R package AdMit D Ardia, LF Hoogerheide, HK Van Dijk Journal of Statistical Software 29, 1-32, 2009 | 45 | 2009 |
| Are education and entrepreneurial income endogenous? A Bayesian analysis JH Block, L Hoogerheide, R Thurik Entrepreneurship Research Journal 2 (3), 2012 | 33 | 2012 |
| Forecast density combinations of dynamic models and data driven portfolio strategies N Baştürk, A Borowska, S Grassi, L Hoogerheide, HK van Dijk Journal of Econometrics 210 (1), 170-186, 2019 | 32 | 2019 |
| Bayesian analysis of instrumental variable models: Acceptance-rejection within Direct Monte Carlo A Zellner, T Ando, N Baştürk, L Hoogerheide, HK Van Dijk Econometric Reviews 33 (1-4), 3-35, 2014 | 32 | 2014 |
| Simulation‐Based Bayesian Econometric Inference: Principles and Some Recent Computational Advances LF Hoogerheide, HK Van Dijk, RD Van Oest Handbook of computational econometrics, 215-280, 2009 | 27 | 2009 |
| Admit: adaptive mixtures of student-t distributions D Ardia, LF Hoogerheide, HK van Dijk The R Journal 1 (1), 25-30, 2009 | 19 | 2009 |
| Essays on Neural Network Sampling Methods and Instrumental Variables L Hoogerheide Rozenberg Publishers, 2006 | 19 | 2006 |
| Efficient Bayesian estimation and combination of GARCH-type models D Ardia, LF Hoogerheide | 18 | 2010 |
| Possible Ill-behaved Posteriors in Econometric Models: On the Connection Between Model Structures, Non-elliptical Credible Sets and Neural Network Simulation Techniques LF Hoogerheide, HK Dijk Tinbergen Institute, 2008 | 17* | 2008 |
