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Linear models / / Shayle R. Searle, Marvin H.J. Gruber
| Linear models / / Shayle R. Searle, Marvin H.J. Gruber |
| Autore | Searle S. R (Shayle R.), <1928-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , 2017 |
| Descrizione fisica | 1 online resource (685 pages) : illustrations, tables |
| Disciplina | 519.535 |
| Collana | Wiley Series in Probability and Statistics |
| Soggetto topico |
Linear models (Statistics)
Experimental design |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-118-95284-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910466119503321 |
Searle S. R (Shayle R.), <1928->
|
||
| Hoboken, New Jersey : , : Wiley, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Linear models / / Shayle R. Searle, Marvin H.J. Gruber
| Linear models / / Shayle R. Searle, Marvin H.J. Gruber |
| Autore | Searle S. R (Shayle R.), <1928-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , 2017 |
| Descrizione fisica | 1 online resource (685 pages) : illustrations, tables |
| Disciplina | 519.535 |
| Collana | Wiley Series in Probability and Statistics |
| Soggetto topico |
Experimental design
Linear models (Statistics) |
| ISBN |
1-118-95284-7
1-118-95285-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910795940103321 |
|
Searle S. R (Shayle R.), <1928->
|
||
| Hoboken, New Jersey : , : Wiley, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Linear models / / Shayle R. Searle, Marvin H.J. Gruber
| Linear models / / Shayle R. Searle, Marvin H.J. Gruber |
| Autore | Searle S. R (Shayle R.), <1928-> |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : Wiley, , 2017 |
| Descrizione fisica | 1 online resource (685 pages) : illustrations, tables |
| Disciplina | 519.535 |
| Collana | Wiley Series in Probability and Statistics |
| Soggetto topico |
Experimental design
Linear models (Statistics) |
| ISBN |
1-118-95284-7
1-118-95285-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910814644203321 |
|
Searle S. R (Shayle R.), <1928->
|
||
| Hoboken, New Jersey : , : Wiley, , 2017 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Linear models [[electronic resource] /] / S. R. Searle
| Linear models [[electronic resource] /] / S. R. Searle |
| Autore | Searle S. R (Shayle R.), <1928-> |
| Pubbl/distr/stampa | New York, : Wiley, c1997 |
| Descrizione fisica | 1 online resource (560 p.) |
| Disciplina |
519.5
519.538 |
| Collana | Wiley classics library |
| Soggetto topico |
Linear models (Statistics)
Statistics |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-283-59289-4
9786613905345 1-118-49178-5 1-118-49176-9 1-118-49177-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Linear Models; Contents; 1. Generalized Inverse Matrices; 1. Introduction; a. Definition and existence; b. An algorithm; 2. Solving linear equations; a. Consistent equations; b. Obtaining solutions; c. Properties of solutions; 3. The Penrose inverse; 4. Other definitions; 5. Symmetric matrices; a. Properties of a generalized inverse; b. Two methods of derivation; 6. Arbitrariness in a generalized inverse; 7. Other results; 8. Exercises; 2. Distributions and Quadratic Forms; 1. Introduction; 2. Symmetric matrices; 3. Positive definiteness; 4. Distributions; a. Multivariate density functions
b. Momentsc. Linear transformations; d. Moment generating functions; e. Univariate normal; f. Multivariate normal; (i) Density function; (ii) Aitken's integral; (iii) Moment generating function; (iv) Marginal distributions; (v) Conditional distributions; (vi) Independence; g. Central χ2, F and t; h. Non-central χ2; i. Non-central F; j . Other non-central distributions; 5. Distribution of quadratic forms; a. Cumulants; b. Distributions; c. Independence; 6. Bilinear forms; 7. The singular normal distribution; 8. Exercises; 3. Regression, or the Full Rank Model; 1. Introduction; a. The model b. Observationsc. Estimation; d. Example; e. The general case of k x-vartables; f. Example (continued); g. Intercept and no-intercept models; h. Example (continued); 2. Deviations from means; 3. Four methods of estimation; a. Ordinary least squares; b. Generalized least squares; c. Maximum likelihood; d. The best linear unbiased estimator (b.l.u.e.); 4. Consequences of estimation; a. Unbiasedness; b. Variances; c. Estimating E(y); d. Residual error sum of squares; e. Estimating the residual error variance; f. Partitioning the total sum of squares; g. Multiple correlation h. Example (continued)5. Distributional properties; a. y is normal; b. b is normal; c. b and σ2 are independent; d. SSE/σ2 has a χ2-distribution; e. Non-central χ2's; f. F-distributions; g. Analyses of variance; h. Pure error; i. Tests of hypotheses; j . Example (continued); k. Confidence intervals; l. Example (continued); 6. The general linear hypothesis; a. Testing linear hypotheses; b. Estimation under the null hypothesis; c. Four common hypotheses; (i) H: b = 0; (ii) H: b = b0; (iii) H: λ'b = m; (iv) H: bq = 0; d. Reduced models; (i) K'b = m; (ii) K'b = 0; (iii) bq = 0; 7. Related topics a. The likelihood ratio testb. Type I and II errors; c. The power of a test; d. Examining residuals; 8. Summary of regression calculations; 9. Exercises; 4. Introducing Linear Models: Regression on Dummy Variables; 1. Regression on allocated codes; a. Allocated codes; b. Difficulties and criticism; c. Grouped variables; d. Unbalanced data; 2. Regression on dummy (0, 1) variables; a. Factors and levels; b. The regression; 3. Describing linear models; a. A 1-way classification; b. A 2-way classification; c. A 3-way classification; d. Main effects and interactions; (i) Main effects (ii) Interactions |
| Record Nr. | UNINA-9910141414903321 |
|
Searle S. R (Shayle R.), <1928->
|
||
| New York, : Wiley, c1997 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Linear models [[electronic resource] /] / S. R. Searle
| Linear models [[electronic resource] /] / S. R. Searle |
| Autore | Searle S. R (Shayle R.), <1928-> |
| Pubbl/distr/stampa | New York, : Wiley, c1997 |
| Descrizione fisica | 1 online resource (560 p.) |
| Disciplina |
519.5
519.538 |
| Collana | Wiley classics library |
| Soggetto topico |
Linear models (Statistics)
Statistics |
| ISBN |
1-283-59289-4
9786613905345 1-118-49178-5 1-118-49176-9 1-118-49177-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Linear Models; Contents; 1. Generalized Inverse Matrices; 1. Introduction; a. Definition and existence; b. An algorithm; 2. Solving linear equations; a. Consistent equations; b. Obtaining solutions; c. Properties of solutions; 3. The Penrose inverse; 4. Other definitions; 5. Symmetric matrices; a. Properties of a generalized inverse; b. Two methods of derivation; 6. Arbitrariness in a generalized inverse; 7. Other results; 8. Exercises; 2. Distributions and Quadratic Forms; 1. Introduction; 2. Symmetric matrices; 3. Positive definiteness; 4. Distributions; a. Multivariate density functions
b. Momentsc. Linear transformations; d. Moment generating functions; e. Univariate normal; f. Multivariate normal; (i) Density function; (ii) Aitken's integral; (iii) Moment generating function; (iv) Marginal distributions; (v) Conditional distributions; (vi) Independence; g. Central χ2, F and t; h. Non-central χ2; i. Non-central F; j . Other non-central distributions; 5. Distribution of quadratic forms; a. Cumulants; b. Distributions; c. Independence; 6. Bilinear forms; 7. The singular normal distribution; 8. Exercises; 3. Regression, or the Full Rank Model; 1. Introduction; a. The model b. Observationsc. Estimation; d. Example; e. The general case of k x-vartables; f. Example (continued); g. Intercept and no-intercept models; h. Example (continued); 2. Deviations from means; 3. Four methods of estimation; a. Ordinary least squares; b. Generalized least squares; c. Maximum likelihood; d. The best linear unbiased estimator (b.l.u.e.); 4. Consequences of estimation; a. Unbiasedness; b. Variances; c. Estimating E(y); d. Residual error sum of squares; e. Estimating the residual error variance; f. Partitioning the total sum of squares; g. Multiple correlation h. Example (continued)5. Distributional properties; a. y is normal; b. b is normal; c. b and σ2 are independent; d. SSE/σ2 has a χ2-distribution; e. Non-central χ2's; f. F-distributions; g. Analyses of variance; h. Pure error; i. Tests of hypotheses; j . Example (continued); k. Confidence intervals; l. Example (continued); 6. The general linear hypothesis; a. Testing linear hypotheses; b. Estimation under the null hypothesis; c. Four common hypotheses; (i) H: b = 0; (ii) H: b = b0; (iii) H: λ'b = m; (iv) H: bq = 0; d. Reduced models; (i) K'b = m; (ii) K'b = 0; (iii) bq = 0; 7. Related topics a. The likelihood ratio testb. Type I and II errors; c. The power of a test; d. Examining residuals; 8. Summary of regression calculations; 9. Exercises; 4. Introducing Linear Models: Regression on Dummy Variables; 1. Regression on allocated codes; a. Allocated codes; b. Difficulties and criticism; c. Grouped variables; d. Unbalanced data; 2. Regression on dummy (0, 1) variables; a. Factors and levels; b. The regression; 3. Describing linear models; a. A 1-way classification; b. A 2-way classification; c. A 3-way classification; d. Main effects and interactions; (i) Main effects (ii) Interactions |
| Record Nr. | UNINA-9910830908403321 |
|
Searle S. R (Shayle R.), <1928->
|
||
| New York, : Wiley, c1997 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Linear models [[electronic resource] /] / S. R. Searle
| Linear models [[electronic resource] /] / S. R. Searle |
| Autore | Searle S. R (Shayle R.), <1928-> |
| Pubbl/distr/stampa | New York, : Wiley, c1997 |
| Descrizione fisica | 1 online resource (560 p.) |
| Disciplina |
519.5
519.538 |
| Collana | Wiley classics library |
| Soggetto topico |
Linear models (Statistics)
Statistics |
| ISBN |
1-283-59289-4
9786613905345 1-118-49178-5 1-118-49176-9 1-118-49177-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Linear Models; Contents; 1. Generalized Inverse Matrices; 1. Introduction; a. Definition and existence; b. An algorithm; 2. Solving linear equations; a. Consistent equations; b. Obtaining solutions; c. Properties of solutions; 3. The Penrose inverse; 4. Other definitions; 5. Symmetric matrices; a. Properties of a generalized inverse; b. Two methods of derivation; 6. Arbitrariness in a generalized inverse; 7. Other results; 8. Exercises; 2. Distributions and Quadratic Forms; 1. Introduction; 2. Symmetric matrices; 3. Positive definiteness; 4. Distributions; a. Multivariate density functions
b. Momentsc. Linear transformations; d. Moment generating functions; e. Univariate normal; f. Multivariate normal; (i) Density function; (ii) Aitken's integral; (iii) Moment generating function; (iv) Marginal distributions; (v) Conditional distributions; (vi) Independence; g. Central χ2, F and t; h. Non-central χ2; i. Non-central F; j . Other non-central distributions; 5. Distribution of quadratic forms; a. Cumulants; b. Distributions; c. Independence; 6. Bilinear forms; 7. The singular normal distribution; 8. Exercises; 3. Regression, or the Full Rank Model; 1. Introduction; a. The model b. Observationsc. Estimation; d. Example; e. The general case of k x-vartables; f. Example (continued); g. Intercept and no-intercept models; h. Example (continued); 2. Deviations from means; 3. Four methods of estimation; a. Ordinary least squares; b. Generalized least squares; c. Maximum likelihood; d. The best linear unbiased estimator (b.l.u.e.); 4. Consequences of estimation; a. Unbiasedness; b. Variances; c. Estimating E(y); d. Residual error sum of squares; e. Estimating the residual error variance; f. Partitioning the total sum of squares; g. Multiple correlation h. Example (continued)5. Distributional properties; a. y is normal; b. b is normal; c. b and σ2 are independent; d. SSE/σ2 has a χ2-distribution; e. Non-central χ2's; f. F-distributions; g. Analyses of variance; h. Pure error; i. Tests of hypotheses; j . Example (continued); k. Confidence intervals; l. Example (continued); 6. The general linear hypothesis; a. Testing linear hypotheses; b. Estimation under the null hypothesis; c. Four common hypotheses; (i) H: b = 0; (ii) H: b = b0; (iii) H: λ'b = m; (iv) H: bq = 0; d. Reduced models; (i) K'b = m; (ii) K'b = 0; (iii) bq = 0; 7. Related topics a. The likelihood ratio testb. Type I and II errors; c. The power of a test; d. Examining residuals; 8. Summary of regression calculations; 9. Exercises; 4. Introducing Linear Models: Regression on Dummy Variables; 1. Regression on allocated codes; a. Allocated codes; b. Difficulties and criticism; c. Grouped variables; d. Unbalanced data; 2. Regression on dummy (0, 1) variables; a. Factors and levels; b. The regression; 3. Describing linear models; a. A 1-way classification; b. A 2-way classification; c. A 3-way classification; d. Main effects and interactions; (i) Main effects (ii) Interactions |
| Record Nr. | UNINA-9910841111103321 |
|
Searle S. R (Shayle R.), <1928->
|
||
| New York, : Wiley, c1997 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Variance components [[electronic resource] /] / Shayle R. Searle, George Casella, Charles E. McCulloch
| Variance components [[electronic resource] /] / Shayle R. Searle, George Casella, Charles E. McCulloch |
| Autore | Searle S. R (Shayle R.), <1928-> |
| Pubbl/distr/stampa | New York, : Wiley, c1992 |
| Descrizione fisica | 1 online resource (537 p.) |
| Disciplina |
519.5
519.538 |
| Altri autori (Persone) |
CasellaGeorge
McCullochCharles E |
| Collana | Wiley series in probability and mathematical statistics. Applied probability and statistics |
| Soggetto topico |
Analysis of variance
Mathematical statistics |
| ISBN |
1-282-30740-1
9786612307409 0-470-31685-3 0-470-31769-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Variance Components; CONTENTS; 1. Introduction; 1.1. Factors, levels, cells and effects; 1.2. Balanced and unbalanced data; a. Balanced data; b. Special cases of unbalanced data; -i. Planned unbalancedness; -ii. Estimating missing observations; c. Unbalanced data; 1.3. Fixed effects and random effects; a. Fixed effects models; Example 1 (Tomato varieties); Example 2 (Medications); Example 3 (Soils and, fertilizers); b. Random eflecrs models; Example 4 (Clinics); Example 5 (Dairy bulls); Example 6 (Ball bearings and calipers); c. Mixed models; Example 7 (Medications and clinics)
Example 8 ( Varieties and gardens)1.4. Fixed or random?; Example 9 (Mice and technicians); 1.5. Finite populations; 1.6. Summary; a. Characteristics of the fixed effects model and the random eflects model for the I-way classification; b. Examples; c. Fixed or random; 2. History and Comment; 2.1. Analysis of variance; 2.2. Early years: 1861-1949; a. Sources; b. Pre-1900; C. 1900-1939; -i. R. A. Fisher; -ii. L. C. Tippett; -iii. The late 1930s; -iv. Unbalanced data; d. The 1940s; 2.3. Great strides: 1950-1969; a. The Henderson methods; b. ANOVA estimation, in general; -i. Negative estimates -ii. Unhiasedness-iii. Best unbiasedness; -iv. Minimal sujicient statistics; -v. Lack of uniqueness; 2.4 Into the 1970s and beyond; a. Maximum likelihood (M L); b. Restricted maximum likelihood (REML); c. Minimum norm estimation; d. The dispersion-mean model; e. Bayes estimation; f: The recent decade; 3. The I-Way Classification; 3.1. The model; a. The model equation; b. First moments; c. Second moments; 3.2. Matrix formulation of the model; a. Example 1; b. The general case; c. Dispersion matrices; -i. The traditional random model; -ii. Other alternatives; d. Unbalanced data; -i. Example 2 -ii. The general case-iii. Dispersion matrix; 3.3 Estimating the mean; 3.4 Predicting random effects; 3.5 ANOVA estimation-balanced data; a. Expected sums of squares; -i. A direct derivation; -ii. Using the matrix formulation; b. ANOVA estimators; c. Negative estimates; d. Normality assumptions; -i. X2-distributions of sums of squares; -ii. Independence of sums of squares; -iii. Sampling variances of estimators; -iv. An F-statistic to test H:σ 2/a =0; -v. Confidence intervals; -vi. Probability of a negative estimate; -vii. Distribution of estimators; 3.6 ANOVA estimation-unbalanced data a. Expected sums of squares-i. A direct derivation; -ii. Using the matrix formulation; b. ANOVA estimators; c. Negative estimates; d. Normality assumptions; -i. X2-distributions of sums oj squares; -ii. Independence of sums of squares; -iii. Sampling variances of estimators; -iv. The eflect of unhalancedness on sampling variances; -v. F-statistics; -vi. Confidence intervals; 3.7. Maximum likelihood estimation; a. Balanced data; -i. Likelihood; -ii. M L equations and their solutions; -iii. ML estimators; -iv. Expected values and bias; -v. Sampling variances; b. Unbalanced data; -i. Likelihood -ii. ML equations and their solutions |
| Record Nr. | UNINA-9910144695603321 |
|
Searle S. R (Shayle R.), <1928->
|
||
| New York, : Wiley, c1992 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Variance components [[electronic resource] /] / Shayle R. Searle, George Casella, Charles E. McCulloch
| Variance components [[electronic resource] /] / Shayle R. Searle, George Casella, Charles E. McCulloch |
| Autore | Searle S. R (Shayle R.), <1928-> |
| Pubbl/distr/stampa | New York, : Wiley, c1992 |
| Descrizione fisica | 1 online resource (537 p.) |
| Disciplina |
519.5
519.538 |
| Altri autori (Persone) |
CasellaGeorge
McCullochCharles E |
| Collana | Wiley series in probability and mathematical statistics. Applied probability and statistics |
| Soggetto topico |
Analysis of variance
Mathematical statistics |
| ISBN |
1-282-30740-1
9786612307409 0-470-31685-3 0-470-31769-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Variance Components; CONTENTS; 1. Introduction; 1.1. Factors, levels, cells and effects; 1.2. Balanced and unbalanced data; a. Balanced data; b. Special cases of unbalanced data; -i. Planned unbalancedness; -ii. Estimating missing observations; c. Unbalanced data; 1.3. Fixed effects and random effects; a. Fixed effects models; Example 1 (Tomato varieties); Example 2 (Medications); Example 3 (Soils and, fertilizers); b. Random eflecrs models; Example 4 (Clinics); Example 5 (Dairy bulls); Example 6 (Ball bearings and calipers); c. Mixed models; Example 7 (Medications and clinics)
Example 8 ( Varieties and gardens)1.4. Fixed or random?; Example 9 (Mice and technicians); 1.5. Finite populations; 1.6. Summary; a. Characteristics of the fixed effects model and the random eflects model for the I-way classification; b. Examples; c. Fixed or random; 2. History and Comment; 2.1. Analysis of variance; 2.2. Early years: 1861-1949; a. Sources; b. Pre-1900; C. 1900-1939; -i. R. A. Fisher; -ii. L. C. Tippett; -iii. The late 1930s; -iv. Unbalanced data; d. The 1940s; 2.3. Great strides: 1950-1969; a. The Henderson methods; b. ANOVA estimation, in general; -i. Negative estimates -ii. Unhiasedness-iii. Best unbiasedness; -iv. Minimal sujicient statistics; -v. Lack of uniqueness; 2.4 Into the 1970s and beyond; a. Maximum likelihood (M L); b. Restricted maximum likelihood (REML); c. Minimum norm estimation; d. The dispersion-mean model; e. Bayes estimation; f: The recent decade; 3. The I-Way Classification; 3.1. The model; a. The model equation; b. First moments; c. Second moments; 3.2. Matrix formulation of the model; a. Example 1; b. The general case; c. Dispersion matrices; -i. The traditional random model; -ii. Other alternatives; d. Unbalanced data; -i. Example 2 -ii. The general case-iii. Dispersion matrix; 3.3 Estimating the mean; 3.4 Predicting random effects; 3.5 ANOVA estimation-balanced data; a. Expected sums of squares; -i. A direct derivation; -ii. Using the matrix formulation; b. ANOVA estimators; c. Negative estimates; d. Normality assumptions; -i. X2-distributions of sums of squares; -ii. Independence of sums of squares; -iii. Sampling variances of estimators; -iv. An F-statistic to test H:σ 2/a =0; -v. Confidence intervals; -vi. Probability of a negative estimate; -vii. Distribution of estimators; 3.6 ANOVA estimation-unbalanced data a. Expected sums of squares-i. A direct derivation; -ii. Using the matrix formulation; b. ANOVA estimators; c. Negative estimates; d. Normality assumptions; -i. X2-distributions of sums oj squares; -ii. Independence of sums of squares; -iii. Sampling variances of estimators; -iv. The eflect of unhalancedness on sampling variances; -v. F-statistics; -vi. Confidence intervals; 3.7. Maximum likelihood estimation; a. Balanced data; -i. Likelihood; -ii. M L equations and their solutions; -iii. ML estimators; -iv. Expected values and bias; -v. Sampling variances; b. Unbalanced data; -i. Likelihood -ii. ML equations and their solutions |
| Record Nr. | UNINA-9910830159603321 |
|
Searle S. R (Shayle R.), <1928->
|
||
| New York, : Wiley, c1992 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Variance components [[electronic resource] /] / Shayle R. Searle, George Casella, Charles E. McCulloch
| Variance components [[electronic resource] /] / Shayle R. Searle, George Casella, Charles E. McCulloch |
| Autore | Searle S. R (Shayle R.), <1928-> |
| Pubbl/distr/stampa | New York, : Wiley, c1992 |
| Descrizione fisica | 1 online resource (537 p.) |
| Disciplina |
519.5
519.538 |
| Altri autori (Persone) |
CasellaGeorge
McCullochCharles E |
| Collana | Wiley series in probability and mathematical statistics. Applied probability and statistics |
| Soggetto topico |
Analysis of variance
Mathematical statistics |
| ISBN |
1-282-30740-1
9786612307409 0-470-31685-3 0-470-31769-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Variance Components; CONTENTS; 1. Introduction; 1.1. Factors, levels, cells and effects; 1.2. Balanced and unbalanced data; a. Balanced data; b. Special cases of unbalanced data; -i. Planned unbalancedness; -ii. Estimating missing observations; c. Unbalanced data; 1.3. Fixed effects and random effects; a. Fixed effects models; Example 1 (Tomato varieties); Example 2 (Medications); Example 3 (Soils and, fertilizers); b. Random eflecrs models; Example 4 (Clinics); Example 5 (Dairy bulls); Example 6 (Ball bearings and calipers); c. Mixed models; Example 7 (Medications and clinics)
Example 8 ( Varieties and gardens)1.4. Fixed or random?; Example 9 (Mice and technicians); 1.5. Finite populations; 1.6. Summary; a. Characteristics of the fixed effects model and the random eflects model for the I-way classification; b. Examples; c. Fixed or random; 2. History and Comment; 2.1. Analysis of variance; 2.2. Early years: 1861-1949; a. Sources; b. Pre-1900; C. 1900-1939; -i. R. A. Fisher; -ii. L. C. Tippett; -iii. The late 1930s; -iv. Unbalanced data; d. The 1940s; 2.3. Great strides: 1950-1969; a. The Henderson methods; b. ANOVA estimation, in general; -i. Negative estimates -ii. Unhiasedness-iii. Best unbiasedness; -iv. Minimal sujicient statistics; -v. Lack of uniqueness; 2.4 Into the 1970s and beyond; a. Maximum likelihood (M L); b. Restricted maximum likelihood (REML); c. Minimum norm estimation; d. The dispersion-mean model; e. Bayes estimation; f: The recent decade; 3. The I-Way Classification; 3.1. The model; a. The model equation; b. First moments; c. Second moments; 3.2. Matrix formulation of the model; a. Example 1; b. The general case; c. Dispersion matrices; -i. The traditional random model; -ii. Other alternatives; d. Unbalanced data; -i. Example 2 -ii. The general case-iii. Dispersion matrix; 3.3 Estimating the mean; 3.4 Predicting random effects; 3.5 ANOVA estimation-balanced data; a. Expected sums of squares; -i. A direct derivation; -ii. Using the matrix formulation; b. ANOVA estimators; c. Negative estimates; d. Normality assumptions; -i. X2-distributions of sums of squares; -ii. Independence of sums of squares; -iii. Sampling variances of estimators; -iv. An F-statistic to test H:σ 2/a =0; -v. Confidence intervals; -vi. Probability of a negative estimate; -vii. Distribution of estimators; 3.6 ANOVA estimation-unbalanced data a. Expected sums of squares-i. A direct derivation; -ii. Using the matrix formulation; b. ANOVA estimators; c. Negative estimates; d. Normality assumptions; -i. X2-distributions of sums oj squares; -ii. Independence of sums of squares; -iii. Sampling variances of estimators; -iv. The eflect of unhalancedness on sampling variances; -v. F-statistics; -vi. Confidence intervals; 3.7. Maximum likelihood estimation; a. Balanced data; -i. Likelihood; -ii. M L equations and their solutions; -iii. ML estimators; -iv. Expected values and bias; -v. Sampling variances; b. Unbalanced data; -i. Likelihood -ii. ML equations and their solutions |
| Record Nr. | UNINA-9910841893103321 |
|
Searle S. R (Shayle R.), <1928->
|
||
| New York, : Wiley, c1992 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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