Extended abstracts fall 2015 : Biomedical Big Data / Guadalupe Gómez, Pere Puig, M.Luz Calle Editors ; Statistics for Low Dose Radiation Research / Elizabeth A. Ainsbury ... [et al.] editors
| Extended abstracts fall 2015 : Biomedical Big Data / Guadalupe Gómez, Pere Puig, M.Luz Calle Editors ; Statistics for Low Dose Radiation Research / Elizabeth A. Ainsbury ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Birkhäuser, 2017 |
| Descrizione fisica | vii, 131 p. : ill. ; 24 cm |
| Soggetto topico |
62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020]
62M10 - Time series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020] 92B15 - General Biostatistics [MSC 2020] 92D30 - Epidemiology [MSC 2020] 92C60 - Medical epidemiology [MSC 2020] 62N01 - Censored data models [MSC 2020] |
| Soggetto non controllato |
Bayesian methods
Epidemiology Genetics HIV research High-Dimensional Data Integrative omics Inverse regression Ionising radiation Low dose Penalized regression Radiation Biology Survival analysis Time series |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0123864 |
| Cham, : Birkhäuser, 2017 | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Extended abstracts fall 2015 : Biomedical Big Data / Guadalupe Gómez, Pere Puig, M.Luz Calle Editors ; Statistics for Low Dose Radiation Research / Elizabeth A. Ainsbury ... [et al.] editors
| Extended abstracts fall 2015 : Biomedical Big Data / Guadalupe Gómez, Pere Puig, M.Luz Calle Editors ; Statistics for Low Dose Radiation Research / Elizabeth A. Ainsbury ... [et al.] editors |
| Pubbl/distr/stampa | Cham, : Birkhäuser, 2017 |
| Descrizione fisica | vii, 131 p. : ill. ; 24 cm |
| Soggetto topico |
62M10 - Time series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020]
62N01 - Censored data models [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] 92B15 - General Biostatistics [MSC 2020] 92C60 - Medical epidemiology [MSC 2020] 92D30 - Epidemiology [MSC 2020] |
| Soggetto non controllato |
Bayesian methods
Epidemiology Genetics HIV research High-Dimensional Data Integrative omics Inverse regression Ionising radiation Low dose Penalized regression Radiation Biology Survival analysis Time series |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00123864 |
| Cham, : Birkhäuser, 2017 | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Modeling discrete time-to-event data / Gerhard Tutz, Matthias Schmid
| Modeling discrete time-to-event data / Gerhard Tutz, Matthias Schmid |
| Autore | Tutz, Gerhard |
| Pubbl/distr/stampa | [Cham], : Springer, 2016 |
| Descrizione fisica | X, 247 p. : ill. ; 24 cm |
| Altri autori (Persone) | Schmid, Matthias |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] 62M10 - Time series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020] 62G05 - Nonparametric estimation [MSC 2020] 62P05 - Applications of statistics to actuarial sciences and financial mathematics [MSC 2020] 62N02 - Estimation in survival analysis and censored data [MSC 2020] 62N03 - Testing in survival analysis and censored data [MSC 2020] |
| Soggetto non controllato |
Additive models
Competing risks Continuation ratio model DiscSurv Discrete frailty model Discrete hazard function Discrete hazard model Generalized estimation equations Goodness-of-Fit Gradient boosting Interval censoring Life tables Multiple spells Penalized regression Recursive partitioning Sequential methods in item response theory Smooth effects Survival data Survival functions Time-dependent AUC Time-to-Event Data |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0114987 |
Tutz, Gerhard
|
||
| [Cham], : Springer, 2016 | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
Modeling discrete time-to-event data / Gerhard Tutz, Matthias Schmid
| Modeling discrete time-to-event data / Gerhard Tutz, Matthias Schmid |
| Autore | Tutz, Gerhard |
| Pubbl/distr/stampa | [Cham], : Springer, 2016 |
| Descrizione fisica | X, 247 p. : ill. ; 24 cm |
| Altri autori (Persone) | Schmid, Matthias |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62G05 - Nonparametric estimation [MSC 2020] 62M10 - Time series, auto-correlation, regression, etc. in statistics (GARCH) [MSC 2020] 62N02 - Estimation in survival analysis and censored data [MSC 2020] 62N03 - Testing in survival analysis and censored data [MSC 2020] 62P05 - Applications of statistics to actuarial sciences and financial mathematics [MSC 2020] 62P10 - Applications of statistics to biology and medical sciences; meta analysis [MSC 2020] |
| Soggetto non controllato |
Additive models
Competing risks Continuation ratio model DiscSurv Discrete frailty model Discrete hazard function Discrete hazard model Generalized estimation equations Goodness-of-fit test Gradient boosting Interval censoring Life tables Multiple spells Penalized regression Recursive partitioning Sequential methods in item response theory Smooth effects Survival data Survival functions Time-dependent AUC Time-to-Event Data |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00114987 |
Tutz, Gerhard
|
||
| [Cham], : Springer, 2016 | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||