A course in mathematical statistics and large sample theory / Rabi Bhattacharya, Lizhen Lin, Victor Patrangenaru |
Autore | Bhattacharya, Rabi |
Pubbl/distr/stampa | New York, : Springer, 2016 |
Descrizione fisica | XI, 389 p. : ill. ; 24 cm |
Altri autori (Persone) |
Lin, Lizhen
Patrangenaru, Victor |
Soggetto topico |
65C05 - Monte Carlo methods [MSC 2020]
62B05 - Sufficient statistics and fields [MSC 2020] 62-XX - Statistics [MSC 2020] 62F03 - Parametric hypothesis testing [MSC 2020] 62M05 - Markov processes: estimation; hidden Markov models [MSC 2020] 62Dxx - Statistical sampling theory and related topics [MSC 2020] 62G05 - Nonparametric estimation [MSC 2020] 62G10 - Nonparametric hypothesis testing [MSC 2020] 62E20 - Asymptotic distribution theory in statistics [MSC 2020] 62G20 - Asymptotic properties of nonparametric inference [MSC 2020] 62C05 - General considerations in statistical decision theory [MSC 2020] 62G09 - Nonparametric statistical resampling methods [MSC 2020] 60J05 - Discrete-time Markov processes on general state spaces [MSC 2020] |
Soggetto non controllato |
Asymptotic Distribution
Bayes estimators Bayes rules Bootstrap Confidence Intervals Cramer-Rao Inequality Curve estimation Decision theory Gauss-Markov Theorem Large sample theory Linear Models Markov Chain Monte Carlo Simulation Neyman-Pearson lemma Nonparametric Parametric Unbiased estimation |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN0114246 |
Bhattacharya, Rabi
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New York, : Springer, 2016 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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A course in mathematical statistics and large sample theory / Rabi Bhattacharya, Lizhen Lin, Victor Patrangenaru |
Autore | Bhattacharya, Rabi |
Pubbl/distr/stampa | New York, : Springer, 2016 |
Descrizione fisica | XI, 389 p. : ill. ; 24 cm |
Altri autori (Persone) |
Lin, Lizhen
Patrangenaru, Victor |
Soggetto topico |
60J05 - Discrete-time Markov processes on general state spaces [MSC 2020]
62-XX - Statistics [MSC 2020] 62B05 - Sufficient statistics and fields [MSC 2020] 62C05 - General considerations in statistical decision theory [MSC 2020] 62Dxx - Statistical sampling theory and related topics [MSC 2020] 62E20 - Asymptotic distribution theory in statistics [MSC 2020] 62F03 - Parametric hypothesis testing [MSC 2020] 62G05 - Nonparametric estimation [MSC 2020] 62G09 - Nonparametric statistical resampling methods [MSC 2020] 62G10 - Nonparametric hypothesis testing [MSC 2020] 62G20 - Asymptotic properties of nonparametric inference [MSC 2020] 62M05 - Markov processes: estimation; hidden Markov models [MSC 2020] 65C05 - Monte Carlo methods [MSC 2020] |
Soggetto non controllato |
Asymptotic Distribution
Bayes estimators Bayes rules Bootstrap Confidence Intervals Cramer-Rao Inequality Curve estimation Decision theory Gauss-Markov Theorem Large sample theory Linear Models Markov Chain Monte Carlo Simulation Neyman-Pearson lemma Nonparametric Parametric Unbiased estimation |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN00114246 |
Bhattacharya, Rabi
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New York, : Springer, 2016 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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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]
62J05 - Linear regression; mixed models [MSC 2020] 62P20 - Applications of statistics to economics [MSC 2020] 62P25 - Applications of statistics to social sciences [MSC 2020] 62D05 - Sampling theory, sample surveys [MSC 2020] |
Soggetto non controllato |
Best linear unbiased prediction
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-VAN0274507 |
Cham, : Springer, 2021 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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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 prediction
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 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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A First Course in Linear Models and Design of Experiments / N. R. Mohan Madhyastha, S. Ravi, A. S. Praveena |
Autore | Madhyastha, N. R. Mohan |
Pubbl/distr/stampa | Singapore, : Springer, 2020 |
Descrizione fisica | xiv, 230 p. : ill. ; 24 cm |
Altri autori (Persone) |
Praveena, Attahalli S.
Ravi, Sreenivasan |
Soggetto topico |
62F10 - Point estimation [MSC 2020]
62J05 - Linear regression; mixed models [MSC 2020] 62Kxx - Design of statistical experiments [MSC 2020] 62K10 - Statistical block designs [MSC 2020] 62F03 - Parametric hypothesis testing [MSC 2020] 62J10 - Analysis of variance and covariance (ANOVA) [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] 62H10 - Multivariate distribution of statistics [MSC 2020] 62F25 - Parametric tolerance and confidence regions [MSC 2020] 62K15 - Factorial statistical designs [MSC 2020] |
Soggetto non controllato |
Analysis of covariance
Analysis of variance Block Designs Design of experiments Factorial experiments Linear Models Linear hypotheses Missing plot technique Row-column designs Split plot experiments Standard designs |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN0250059 |
Madhyastha, N. R. Mohan
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Singapore, : Springer, 2020 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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A First Course in Linear Models and Design of Experiments / N. R. Mohan Madhyastha, S. Ravi, A. S. Praveena |
Autore | Madhyastha, N. R. Mohan |
Pubbl/distr/stampa | Singapore, : Springer, 2020 |
Descrizione fisica | xiv, 230 p. : ill. ; 24 cm |
Altri autori (Persone) |
Praveena, Attahalli S.
Ravi, Sreenivasan |
Soggetto topico |
62F03 - Parametric hypothesis testing [MSC 2020]
62F10 - Point estimation [MSC 2020] 62F25 - Parametric tolerance and confidence regions [MSC 2020] 62H10 - Multivariate distribution of statistics [MSC 2020] 62J05 - Linear regression; mixed models [MSC 2020] 62J10 - Analysis of variance and covariance (ANOVA) [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] 62K10 - Statistical block designs [MSC 2020] 62K15 - Factorial statistical designs [MSC 2020] 62Kxx - Design of statistical experiments [MSC 2020] |
Soggetto non controllato |
Analysis of covariance
Analysis of variance Block Designs Design of experiments Factorial experiments Linear Models Linear hypotheses Missing plot technique Row-column designs Split plot experiments Standard designs |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN00250059 |
Madhyastha, N. R. Mohan
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Singapore, : Springer, 2020 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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Applications of Linear and Nonlinear Models : Fixed Effects, Random Effects, and Total Least Squares / Erik W. Grafarend, Silvelyn Zwanzig, Joseph L. Awange |
Autore | Grafarend, Erik W. |
Edizione | [2. ed] |
Pubbl/distr/stampa | Cham, : Springer, 2022 |
Descrizione fisica | xxv, 1113 p. : ill. ; 24 cm |
Altri autori (Persone) |
Awange, Joseph L.
Zwanzig, Silvelyn |
Soggetto non controllato |
Adjustment
Geodesy Linear Models Mathematical statistics Nonlinear models |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNICAMPANIA-VAN0276875 |
Grafarend, Erik W.
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Cham, : Springer, 2022 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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Applications of Linear and Nonlinear Models : Fixed Effects, Random Effects, and Total Least Squares / Erik W. Grafarend, Silvelyn Zwanzig, Joseph L. Awange |
Autore | Grafarend, Erik W. |
Edizione | [2. ed] |
Pubbl/distr/stampa | Cham, : Springer, 2022 |
Descrizione fisica | xxv, 1113 p. : ill. ; 24 cm |
Altri autori (Persone) |
Awange, Joseph L.
Zwanzig, Silvelyn |
Soggetto topico |
62-XX - Statistics [MSC 2020]
62Jxx - Linear inference, regression [MSC 2020] 62Pxx - Applications of statistics [MSC 2020] |
Soggetto non controllato |
Adjustment
Geodesy Linear Models Mathematical statistics Nonlinear models |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNICAMPANIA-VAN00276875 |
Grafarend, Erik W.
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Cham, : Springer, 2022 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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Basics of Modern Mathematical Statistics / Vladimir Spokoiny, Thorsten Dickhaus |
Autore | Spokoiny, Vladimir |
Pubbl/distr/stampa | Berlin, : Springer, 2015 |
Descrizione fisica | xviii, 296 p. ; 24 cm |
Altri autori (Persone) | Dickhaus, Thorsten |
Soggetto topico |
62Hxx - Multivariate analysis [MSC 2020]
62Jxx - Linear inference, regression [MSC 2020] 62Fxx - Parametric inference [MSC 2020] |
Soggetto non controllato |
Coverage and Concentration
Estimators and Tests Exponential Family Linear Models Maximum Likelihood |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN0125279 |
Spokoiny, Vladimir
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Berlin, : Springer, 2015 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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Basics of Modern Mathematical Statistics / Vladimir Spokoiny, Thorsten Dickhaus |
Autore | Spokoiny, Vladimir |
Pubbl/distr/stampa | Berlin, : Springer, 2015 |
Descrizione fisica | xviii, 296 p. ; 24 cm |
Altri autori (Persone) | Dickhaus, Thorsten |
Soggetto topico |
62Fxx - Parametric inference [MSC 2020]
62Hxx - Multivariate analysis [MSC 2020] 62Jxx - Linear inference, regression [MSC 2020] |
Soggetto non controllato |
Coverage and Concentration
Estimators and Tests Exponential Family Linear Models Maximum Likelihood |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Titolo uniforme | |
Record Nr. | UNICAMPANIA-VAN00125279 |
Spokoiny, Vladimir
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Berlin, : Springer, 2015 | ||
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Lo trovi qui: Univ. Vanvitelli | ||
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