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A Course on Small Area Estimation and Mixed Models : Methods, Theory and Applications in R / Domingo Morales ... [et al.]
| A Course on Small Area Estimation and Mixed Models : Methods, Theory and Applications in R / Domingo Morales ... [et al.] |
| Pubbl/distr/stampa | Cham, : Springer, 2021 |
| Descrizione fisica | xx, 599 p. : ill. ; 24 cm |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62D05 - Sampling theory, sample surveys [MSC 2020] 62J05 - Linear regression; mixed models [MSC 2020] 62P20 - Applications of statistics to economics [MSC 2020] 62P25 - Applications of statistics to social sciences [MSC 2020] |
| Soggetto non controllato |
Best linear unbiased predictors
Design-based estimation Empirical best prediction Estimation of socioeconomic indicators Generalized linear mixed model Labor markets surveys Linear Models Linear mixed models Living conditions surveys Mean squared error estimation Nested error regression models Prediction Theory R code R packages for SAE Small area estimation Survey Methodology |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00274507 |
| Cham, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
The Design and Analysis of Computer Experiments / Thomas J. Santner, Brian J. Williams, William I. Notz
| The Design and Analysis of Computer Experiments / Thomas J. Santner, Brian J. Williams, William I. Notz |
| Autore | Santner, Thomas J. |
| Edizione | [2. ed] |
| Pubbl/distr/stampa | New York, : Springer, 2018 |
| Descrizione fisica | xv, 436 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Notz, William I.
Williams, Brian J. |
| Soggetto topico |
68U07 - Computer science aspects of computer-aided design [MSC 2020]
62-XX - Statistics [MSC 2020] 62Kxx - Design of statistical experiments [MSC 2020] |
| Soggetto non controllato |
Bayesian Inference
Best linear unbiased predictors Calibrationlog likelihood functions Computer experiment Experimental designs Gaussian Process models Heuristic global approximation Latin hypercube designs Sensitivity analysis Simulator output Stochastic process models Variable screening |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0125105 |
Santner, Thomas J.
|
||
| New York, : Springer, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||
The Design and Analysis of Computer Experiments / Thomas J. Santner, Brian J. Williams, William I. Notz
| The Design and Analysis of Computer Experiments / Thomas J. Santner, Brian J. Williams, William I. Notz |
| Autore | Santner, Thomas J. |
| Edizione | [2. ed] |
| Pubbl/distr/stampa | New York, : Springer, 2018 |
| Descrizione fisica | xv, 436 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Notz, William I.
Williams, Brian J. |
| Soggetto topico |
62-XX - Statistics [MSC 2020]
62Kxx - Design of statistical experiments [MSC 2020] 68U07 - Computer science aspects of computer-aided design [MSC 2020] |
| Soggetto non controllato |
Bayesian Inference
Best linear unbiased predictors Calibrationlog likelihood functions Computer experiment Experimental designs Gaussian Process models Heuristic global approximation Latin hypercube designs Sensitivity analysis Simulator output Stochastic process models Variable screening |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00125105 |
|
Santner, Thomas J.
|
||
| New York, : Springer, 2018 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||