1.

Record Nr.

UNINA990001819090403321

Autore

Tortorelli, Nicola

Titolo

L'allevamento della pecora / Nicola Tortorelli

Pubbl/distr/stampa

Bologna : Edagricole, 1961

Edizione

[2.]

Descrizione fisica

111 p. ; 21 cm

Disciplina

636.3

Locazione

FAGBC

Collocazione

60 DONO SARLI 87

Lingua di pubblicazione

Italiano

Formato

Materiale a stampa

Livello bibliografico

Monografia

2.

Record Nr.

UNINA9910143714703321

Autore

Goldstein Michael <1949->

Titolo

Bayes linear statistics [[electronic resource] ] : theory and methods / / Michael Goldstein and David Wooff

Pubbl/distr/stampa

Chichester, England ; ; Hoboken, NJ, : John Wiley, c2007

ISBN

1-280-85495-2

9786610854950

0-470-06566-4

0-470-06567-2

Descrizione fisica

1 online resource (538 p.)

Collana

Wiley series in probability and statistics

Altri autori (Persone)

WooffDavid

Disciplina

519.5

519.542

Soggetti

Bayesian statistical decision theory

Linear systems

Computational complexity

Electronic books.

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia



Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references (p. [497]-502) and index.

Nota di contenuto

Bayes Linear Statistics; Contents; Preface; 1 The Bayes linear approach; 1.1 Combining beliefs with data; 1.2 The Bayesian approach; 1.3 Features of the Bayes linear approach; 1.4 Example; 1.4.1 Expectation, variance, and standardization; 1.4.2 Prior inputs; 1.4.3 Adjusted expectations; 1.4.4 Adjusted versions; 1.4.5 Adjusted variances; 1.4.6 Checking data inputs; 1.4.7 Observed adjusted expectations; 1.4.8 Diagnostics for adjusted beliefs; 1.4.9 Further diagnostics for the adjusted versions; 1.4.10 Summary of basic adjustment; 1.4.11 Diagnostics for collections

1.4.12 Exploring collections of beliefs via canonical structure1.4.13 Modifying the original specifications; 1.4.14 Repeating the analysis for the revised model; 1.4.15 Global analysis of collections of observations; 1.4.16 Partial adjustments; 1.4.17 Partial diagnostics; 1.4.18 Summary; 1.5 Overview; 2 Expectation; 2.1 Expectation as a primitive; 2.2 Discussion: expectation as a primitive; 2.3 Quantifying collections of uncertainties; 2.4 Specifying prior beliefs; 2.4.1 Example: oral glucose tolerance test; 2.5 Qualitative and quantitative prior specification

2.6 Example: qualitative representation of uncertainty2.6.1 Identifying the quantities of interest; 2.6.2 Identifying relevant prior information; 2.6.3 Sources of variation; 2.6.4 Representing population variation; 2.6.5 The qualitative representation; 2.6.6 Graphical models; 2.7 Example: quantifying uncertainty; 2.7.1 Prior expectations; 2.7.2 Prior variances; 2.7.3 Prior covariances; 2.7.4 Summary of belief specifications; 2.8 Discussion: on the various methods for assigning expectations; 3 Adjusting beliefs; 3.1 Adjusted expectation; 3.2 Properties of adjusted expectation

3.3 Adjusted variance3.4 Interpretations of belief adjustment; 3.5 Foundational issues concerning belief adjustment; 3.6 Example: one-dimensional problem; 3.7 Collections of adjusted beliefs; 3.8 Examples; 3.8.1 Algebraic example; 3.8.2 Oral glucose tolerance test; 3.8.3 Many oral glucose tolerance tests; 3.9 Canonical analysis for a belief adjustment; 3.9.1 Canonical directions for the adjustment; 3.9.2 The resolution transform; 3.9.3 Partitioning the resolution; 3.9.4 The reverse adjustment; 3.9.5 Minimal linear sufficiency; 3.9.6 The adjusted belief transform matrix

3.10 The geometric interpretation of belief adjustment3.11 Examples; 3.11.1 Simple one-dimensional problem; 3.11.2 Algebraic example; 3.11.3 Oral glucose tolerance test; 3.12 Further reading; 4 The observed adjustment; 4.1 Discrepancy; 4.1.1 Discrepancy for a collection; 4.1.2 Evaluating discrepancy over a basis; 4.1.3 Discrepancy for quantities with variance zero; 4.2 Properties of discrepancy measures; 4.2.1 Evaluating the discrepancy vector over a basis; 4.3 Examples; 4.3.1 Simple one-dimensional problem; 4.3.2 Detecting degeneracy; 4.3.3 Oral glucose tolerance test

4.4 The observed adjustment

Sommario/riassunto

Bayesian methods combine information available from data with any prior information available from expert knowledge. The Bayes linear approach follows this path, offering a quantitative structure for expressing beliefs, and systematic methods for adjusting these beliefs, given observational data. The methodology differs from the full Bayesian methodology in that it establishes simpler approaches to belief specification and analysis based around expectation judgements. Bayes Linear Statistics presents an authoritative account of this approach, explaining the foundations, theory, methodol



3.

Record Nr.

UNISALENTO991003993179707536

Autore

Gebhart, Émile

Titolo

L'Italia mistica : storia del rinascimento religioso nel Medioevo / Emilio Gebhart ; traduzione di Armando Perotti

Pubbl/distr/stampa

Bari : Gius. Laterza & Figli, 1924

Titolo uniforme

L'Italie mystique. Histoire de la renaissance religieuse au Moyen Âge

Edizione

[2. ed.]

Descrizione fisica

251 p. ; 21 cm

Collana

Biblioteca di cultura moderna ; 40

Disciplina

270.5

Soggetti

Monachesimo

Italia - Storia religiosa - Medioevo

Mistici italiani

Lingua di pubblicazione

Non definito

Formato

Materiale a stampa

Livello bibliografico

Monografia