|
|
|
|
| LEADER |
01000naa a22002652 4500 |
| 001 |
NLM34229184X |
| 003 |
DE-627 |
| 005 |
20231226013750.0 |
| 007 |
cr uuu---uuuuu |
| 008 |
231226s2022 xx |||||o 00| ||eng c |
| 024 |
7 |
|
|a 10.1080/02664763.2020.1803812
|2 doi
|
| 028 |
5 |
2 |
|a pubmed24n1140.xml
|
| 035 |
|
|
|a (DE-627)NLM34229184X
|
| 035 |
|
|
|a (NLM)35707795
|
| 040 |
|
|
|a DE-627
|b ger
|c DE-627
|e rakwb
|
| 041 |
|
|
|a eng
|
| 100 |
1 |
|
|a Vasconcelos, J C S
|e verfasserin
|4 aut
|
| 245 |
1 |
4 |
|a The semiparametric regression model for bimodal data with different penalized smoothers applied to climatology, ethanol and air quality data
|
| 264 |
|
1 |
|c 2022
|
| 336 |
|
|
|a Text
|b txt
|2 rdacontent
|
| 337 |
|
|
|a ƒaComputermedien
|b c
|2 rdamedia
|
| 338 |
|
|
|a ƒa Online-Ressource
|b cr
|2 rdacarrier
|
| 500 |
|
|
|a Date Revised 16.06.2022
|
| 500 |
|
|
|a published: Electronic-eCollection
|
| 500 |
|
|
|a Citation Status PubMed-not-MEDLINE
|
| 520 |
|
|
|a © 2020 Informa UK Limited, trading as Taylor & Francis Group.
|
| 520 |
|
|
|a Semiparametric regressions can be used to model data when covariables and the response variable have a nonlinear relationship. In this work, we propose three flexible regression models for bimodal data called the additive, additive partial and semiparametric regressions, basing on the odd log-logistic generalized inverse Gaussian distribution under three types of penalized smoothers, where the main idea is not to confront the three forms of smoothings but to show the versatility of the distribution with three types of penalized smoothers. We present several Monte Carlo simulations carried out for different configurations of the parameters and some sample sizes to verify the precision of the penalized maximum-likelihood estimators. The usefulness of the proposed regressions is proved empirically through three applications to climatology, ethanol and air quality data
|
| 650 |
|
4 |
|a Journal Article
|
| 650 |
|
4 |
|a Additive model
|
| 650 |
|
4 |
|a additive partial model
|
| 650 |
|
4 |
|a generalized inverse Gaussian distribution
|
| 650 |
|
4 |
|a semiparametric model
|
| 650 |
|
4 |
|a splines
|
| 700 |
1 |
|
|a Cordeiro, G M
|e verfasserin
|4 aut
|
| 700 |
1 |
|
|a Ortega, E M M
|e verfasserin
|4 aut
|
| 773 |
0 |
8 |
|i Enthalten in
|t Journal of applied statistics
|d 1991
|g 49(2022), 1 vom: 17., Seite 248-267
|w (DE-627)NLM098188178
|x 0266-4763
|7 nnns
|
| 773 |
1 |
8 |
|g volume:49
|g year:2022
|g number:1
|g day:17
|g pages:248-267
|
| 856 |
4 |
0 |
|u http://dx.doi.org/10.1080/02664763.2020.1803812
|3 Volltext
|
| 912 |
|
|
|a GBV_USEFLAG_A
|
| 912 |
|
|
|a SYSFLAG_A
|
| 912 |
|
|
|a GBV_NLM
|
| 912 |
|
|
|a GBV_ILN_350
|
| 951 |
|
|
|a AR
|
| 952 |
|
|
|d 49
|j 2022
|e 1
|b 17
|h 248-267
|