Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Didier Nibbering"'
Autor:
Ruben Loaiza-Maya, Didier Nibbering
Publikováno v:
Journal of Business & Economic Statistics. 40:1678-1690
The multinomial probit model is a popular tool for analyzing choice behaviour as it allows for correlation between choice alternatives. Because current model specifications employ a full covariance matrix of the latent utilities for the choice altern
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee9c829eab295751406f54f4c33246c3
https://doi.org/10.1080/07350015.2021.1961788
https://doi.org/10.1080/07350015.2021.1961788
Autor:
Rubén Loaiza-Maya, Didier Nibbering
The multinomial probit model is often used to analyze choice behaviour. However, estimation with existing Markov chain Monte Carlo (MCMC) methods is computationally costly, which limits its applicability to large choice data sets. This paper proposes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87392f0efa823c5da4bf54cc254f33c7
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6e5e90bbcf4478cdef13359c5a9a8deb
https://doi.org/10.2139/ssrn.4058313
https://doi.org/10.2139/ssrn.4058313
Autor:
Tom Boot, Didier Nibbering
Publikováno v:
Journal of Econometrics, 209(2), 391-406. Elsevier Science
textabstractRandom subspace methods are a novel approach to obtain accurate forecasts in high-dimensional regression settings. We provide a theoretical justification of the use of random subspace methods and show their usefulness when forecasting mon
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3c804d1d1b9c343f318e1b04704c6e66
https://hdl.handle.net/11370/c611aba6-97c3-4212-b1df-16e637f40bf2
https://hdl.handle.net/11370/c611aba6-97c3-4212-b1df-16e637f40bf2
Autor:
Didier Nibbering, Bruno Jacobs
Publikováno v:
SSRN Electronic Journal.
A large product assortment is typically characterized by many products that are rarely purchased: the long tail. Combined, these products make a sizable contribution to the total purchase volume. A retailer that better understands the purchase behavi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca3cd104d132e39e374cd9e37d2296ad
https://doi.org/10.2139/ssrn.3915874
https://doi.org/10.2139/ssrn.3915874
Autor:
Trevor Hastie, Didier Nibbering
Publikováno v:
Computational Statistics & Data Analysis. 169:107414
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46a75928e4da1cb789e7c1301e9b86e7
https://doi.org/10.1016/j.csda.2021.107414
https://doi.org/10.1016/j.csda.2021.107414
Publikováno v:
International Journal of Forecasting, 34(2), 288-311. Elsevier
This paper studies what professional forecasters predict. We use spectral analysis and state space modeling to decompose economic time series into trend, business cycle, and irregular components. We examine which components are captured by profession
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41ae73db686b0a368d85cabf2bb6109e
https://pure.eur.nl/en/publications/9692dd86-7eb6-4165-9acd-8096eb670315
https://pure.eur.nl/en/publications/9692dd86-7eb6-4165-9acd-8096eb670315
Autor:
Didier Nibbering, Tom Boot
Publikováno v:
SSRN Electronic Journal.
We introduce an asymptotically unbiased estimator for the full high-dimensional parameter vector in linear regression models where the number of variables exceeds the number of available observations. The estimator is accompanied by a closed-form exp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b1a39549e5f4b33784cd01d03f45932c
https://doi.org/10.2139/ssrn.2932785
https://doi.org/10.2139/ssrn.2932785
Publikováno v:
SSRN Electronic Journal.
We propose a Bayesian infinite hidden Markov model to estimate time-varying parameters in a vector autoregressive model. The Markov structure allows for heterogeneity over time while accounting for state-persistence. By modelling the transition distr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cdb23449913d51c2e649899a483fed0e
https://doi.org/10.2139/ssrn.2882463
https://doi.org/10.2139/ssrn.2882463
Publikováno v:
SSRN Electronic Journal.
In this paper we study what professional forecasters actually explain. We use spectral analysis and state space modeling to decompose economic time series into a trend, a business-cycle, and an irregular component. To examine which components are cap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92cfc9628ea8acbc14488ca5ef56d39d
https://doi.org/10.2139/ssrn.2640878
https://doi.org/10.2139/ssrn.2640878