| 000 | 01388nam a22002777a 4500 | ||
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| 003 | ZW-GwMSU | ||
| 005 | 20240502092907.0 | ||
| 008 | 230626b |||||||| |||| 00| 0 eng d | ||
| 022 | _a13504851 | ||
| 040 |
_aMSU _cMSU _erda _bEnglish |
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| 050 | 0 | 0 | _aHB1.A666 APP |
| 100 | 1 |
_aBelloc, Filippo _eauthor |
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| 245 | 1 | 2 |
_aA dynamic hurdle model for zeroinflated panel count data _ccreated by Filippo Belloc , Mauro Bernardi , Antonello Maruotti and Lea Petrella |
| 264 | 1 |
_aNew York: _bTaylor and Francis, _c2013 |
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| 336 |
_2rdacontent _atext _btxt |
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| 337 |
_2rdamedia _aunmediated _bn |
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| 338 |
_2rdacarrier _avolume _bnc |
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| 440 |
_aApplied economics letters _vVolume 20, number 9 |
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| 520 | 3 | _aThis article proposes an approximate conditional dynamic finite mixture hurdle model for panel count data with excess of zeros and endogenous initial conditions. We provide parameter estimates by using the Expectation-Maximization (EM) algorithm in a Nonparametric Maximum Likelihood (NPML) framework. An application to a unique data set on traffic violation counts of a subpopulation of Italian drivers is given. | |
| 650 |
_aHurdle model _vDynamic models _xFinite mixture |
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| 700 | 1 |
_aBernardi, Mauro _eco-author |
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| 700 | 1 |
_aMaurotti, Antonello _eco-author |
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| 700 | 1 |
_aPetrella, Lea _eco-author |
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| 856 | _uhttps://doi.org/10.1080/13504851.2012.750447 | ||
| 942 |
_2lcc _cJA |
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| 999 |
_c162702 _d162702 |
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