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~subject:"Mixed Logit"
~subject:"Schätztheorie"
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Search: subject:"multinomial probit"
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Mixed Logit
Schätztheorie
multinomial probit
42
Probit-Modell
20
Probit model
18
multinomial probit model
18
Multinomial Probit
14
Multinomial probit
13
Multinomial probit model
12
Theorie
12
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11
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11
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9
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8
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unobserved heterogeneity
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Diskrete Entscheidung
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endogenous fertility decisions
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heterogeneous children effects
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multinomial probit models
6
Discrete Choice
5
Estimation theory
5
Income Segregation
5
Location Choice
5
Monte Carlo simulation
5
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5
USA
5
education
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feedback effects
5
heterogeneity
5
marketing-instrument effectiveness
5
simulated maximum likelihood estimation
5
state dependence
5
trivariate multinomial probit
5
Alternative energy sources and propulsion technologies in vehicles
4
Consumer behaviour
4
Factor analysis
4
Gibbs sampling
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Schmidheiny, Kurt
5
Loiza-Maya, Ruben
3
Nibbering, Didier
3
Bhat, Chandra R.
1
Gensowski, Miriam
1
Lavieri, Patrícia S.
1
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Journal of business & economic statistics : JBES ; a publication of the American Statistical Association
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Theory and decision : an international journal for multidisciplinary advances in decision science
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ECONIS (ZBW)
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1
Fast variational Bayes methods for
multinomial
probit
models
Loiza-Maya, Ruben
;
Nibbering, Didier
- In:
Journal of business & economic statistics : JBES ; a …
41
(
2023
)
4
,
pp. 1352-1363
Persistent link: https://www.econbiz.de/10014448653
Saved in:
2
Scalable Bayesian estimation in the
multinomial
probit
model
Loiza-Maya, Ruben
;
Nibbering, Didier
-
2020
Persistent link: https://www.econbiz.de/10012608350
Saved in:
3
Scalable Bayesian estimation in the
multinomial
probit
model
Loiza-Maya, Ruben
;
Nibbering, Didier
- In:
Journal of business & economic statistics : JBES ; a …
40
(
2022
)
4
,
pp. 1678-1690
Persistent link: https://www.econbiz.de/10013540448
Saved in:
4
A
multinomial
probit
model with latent factors : identification and interpretation without a measurement system
Piatek, Rémi
;
Gensowski, Miriam
-
2017
We develop a parametrization of the
multinomial
probit
model that yields greater insight into the underlying decision …
Persistent link: https://www.econbiz.de/10011732373
Saved in:
5
A new mixed MNP model accommodating a variety of dependent non-normal coefficient distributions
Bhat, Chandra R.
;
Lavieri, Patrícia S.
- In:
Theory and decision : an international journal for …
84
(
2018
)
2
,
pp. 239-275
Persistent link: https://www.econbiz.de/10011940887
Saved in:
6
Income Segregation and Local Progressive Taxation: Empirical Evidence from Switzerland
Schmidheiny, Kurt
-
HWWA Institut für Wirtschaftsforschung
-
2003
econometric spezifications of the error term structure, such as conditional logit, nested logit and
multinomial
probit
are …
Persistent link: https://www.econbiz.de/10010957401
Saved in:
7
Income Segregation and Local Progressive Taxation: Empirical Evidence from Switzerland
Schmidheiny, Kurt
-
2003
econometric spezifications of the error term structure, such as conditional logit, nested logit and
multinomial
probit
are …
Persistent link: https://www.econbiz.de/10010295381
Saved in:
8
Income Segregation and Local Progressive Taxation: Empirical Evidence from Switzerland
Schmidheiny, Kurt
-
2003
econometric spezifications of the error term structure, such as conditional logit, nested logit and
multinomial
probit
are …
Persistent link: https://www.econbiz.de/10009442367
Saved in:
9
Income Segregation and Local Progressive Taxation: Empirical Evidence from Switzerland
Schmidheiny, Kurt
-
HWWA Institut für Wirtschaftsforschung
-
2003
econometric spezifications of the error term structure, such as conditional logit, nested logit and
multinomial
probit
are …
Persistent link: https://www.econbiz.de/10005513596
Saved in:
10
Income Segregation and Local Progressive Taxation: Empirical Evidence from Switzerland
Schmidheiny, Kurt
-
Department Volkswirtschaftlehre, Universität Bern
-
2003
econometric specifications of the error term structure, such as conditional logit, nested logit and
multinomial
probit
are …
Persistent link: https://www.econbiz.de/10005515679
Saved in:
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