Zobrazeno 1 - 10
of 134
pro vyhledávání: '"Walter Zucchini"'
Publikováno v:
Swiss Journal of Economics and Statistics, Vol 152, Iss 1, Pp 49-80 (2016)
Summary We present an integration based procedure for predicting the distribution f of an indicator of interest in situations where, in addition to the sample data, one has access to covariates that are available for the entire population. The propos
Externí odkaz:
https://doaj.org/article/9b80b1f0c66b4b378ad4d976517cddff
Publikováno v:
The Journal of Economic Inequality. 16:439-454
This paper analyzes several modifications to improve a simple measure of vulnerability as expected poverty. Firstly, in order to model income, we apply distributional regression relating potentially each parameter of the conditional income distributi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f47648a5418da417b9fa892006e12e54
https://doi.org/10.1007/s10888-017-9374-6
https://doi.org/10.1007/s10888-017-9374-6
Publikováno v:
Open Journal of Statistics. :545-553
In several instances of statistical practice, it is not uncommon to use the same data for both model selection and inference, without taking account of the variability induced by model selection step. This is usually referred to as post-model selecti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::80ced63669991523331c639a425c223b
https://doi.org/10.4236/ojs.2016.63046
https://doi.org/10.4236/ojs.2016.63046
Publikováno v:
Applied Mathematics. :1103-1115
It is quite common in statistical modeling to select a model and make inference as if the model had been known in advance; i.e. ignoring model selection uncertainty. The resulted estimator is called post-model selection estimator (PMSE) whose propert
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b840fede01440ae6eb4047c981434ea6
https://doi.org/10.4236/am.2016.710098
https://doi.org/10.4236/am.2016.710098
Publikováno v:
Open Journal of Statistics. :220-228
Bayesian model averaging (BMA) is a popular and powerful statistical method of taking account of uncertainty about model form or assumption. Usually the long run (frequentist) performances of the resulted estimator are hard to derive. This paper prop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c961c4e5131a8d669cfa04e2fd7f182c
https://doi.org/10.4236/ojs.2016.62019
https://doi.org/10.4236/ojs.2016.62019
Publikováno v:
Hidden Markov Models for Time Series ISBN: 9781315372488
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::878b390443dc7e58a8b453ac35ab74c6
https://doi.org/10.1201/b20790-14
https://doi.org/10.1201/b20790-14
Publikováno v:
Hidden Markov Models for Time Series ISBN: 9781315372488
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8fdb059b099a786900c62028e63e95a
https://doi.org/10.1201/b20790-17
https://doi.org/10.1201/b20790-17
Publikováno v:
Hidden Markov Models for Time Series ISBN: 9781315372488
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c6e443e0b817ae9fc02d7869bd9dec97
https://doi.org/10.1201/b20790-21
https://doi.org/10.1201/b20790-21
Publikováno v:
Hidden Markov Models for Time Series ISBN: 9781315372488
Hidden Markov Models for Time Series
Hidden Markov Models for Time Series
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::44c524dfc8255d4b5fd040b7594a55d8
https://doi.org/10.1201/b20790-16
https://doi.org/10.1201/b20790-16
Publikováno v:
Hidden Markov Models for Time Series ISBN: 9781315372488
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8ae3922ad80326697ce0fce38cac7787
https://doi.org/10.1201/b20790-10
https://doi.org/10.1201/b20790-10