Registro Completo
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Biblioteca(s): |
Embrapa Florestas. |
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Data corrente: |
14/07/2004 |
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Data da última atualização: |
31/07/2017 |
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Tipo da produção científica: |
Documentos |
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Autoria: |
RESENDE, M. D. V. de; THOMPSON, R. |
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Afiliação: |
Resende, Pesquisador da Embrapa Florestas. |
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Título: |
Multivariate spatial statistical analysis of multiple experiments and longitudinal data. |
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Ano de publicação: |
2003 |
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Fonte/Imprenta: |
Colombo: Embrapa Florestas, 2003. |
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Páginas: |
126 p. |
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Série: |
(Embrapa Florestas. Documentos, 90). |
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ISSN: |
1517-536X |
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Idioma: |
Inglês
Português |
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Conteúdo: |
Multivariate Spatial Statistical Analysis of Longitudinal Data. Introduction. Description of Models. General Linear Mixed Model and REML Estimation. Univariate Spatial Models for Individual Annual Measures on each Trial. Longitudinal Non-Spatial Models for Several Measures on each Trial. Longitudinal Spatial Models for Repeated Measures on each Trial. Model Fitting Procedure and Model Comparisons. Applications. Univariate Spatial Models for Individual Annual Measures on each Trial. Longitudinal Non-Spatial Models for Several Measures on each Trial. Longitudinal Spatial Models for Repeated Measures on each Trial. Conclusions. Factor Analytic Multiplicative Mixed Models in the Analysis of Multiple Experiments. Introduction. Factor Analytic Models. General Linear Mixed Model and REML Estimation of Factor Analytic, Multivariate and Spatial Models. Constraints and Rotation on Loadings and interpretation of Environmental Loadings and Factorial Scores. Goodness of Fit, Model Comparison and Fitting Procedure. Applications. Eucalypt Data Set. Tea Plant Data Set. Conclusions. Analysis of Interference and Environmental Trend in Field Trials by Joint Modelling of Competition and Spatial Variability. Introduction. Competition Models. Phenotypic Interference. Genotypic Interference. Joint Modelling of Competition Effects and Fertility Trends. Competition Models in Perennial Crops and Forest Trees. Proposed Competition and Spatial Models for Perennial Plants. Competition and Spatial Model for Single Tree Plot Design (Four Neighbours). Competition Model for Single Tree Plot Design (Eight Neighbours). Competition and Spatial Model for Multiple Tree Plot Design (Four Neighbours). Competition and Spatial Model for Multiple Tree Plot Design (Eight Neighbours). Generalised Competition and Spatial Model. Phenotypic Competition and Spatial Model. Missing Plant Effects. Profile Likelihood and Generalisation of REML (GREML). Estimation/Prediction Procedures and Software. Applications to Experimental Data. General Results from Five Different Species. Phenotypic Competition Models via Profile Likelihood in Sugarcane. Genotypic and Phenotypic Competition Models in Eucalyptus maculata. Genotypic and Phenotypic Competition Models in Pinus. Conclusions. References. MenosMultivariate Spatial Statistical Analysis of Longitudinal Data. Introduction. Description of Models. General Linear Mixed Model and REML Estimation. Univariate Spatial Models for Individual Annual Measures on each Trial. Longitudinal Non-Spatial Models for Several Measures on each Trial. Longitudinal Spatial Models for Repeated Measures on each Trial. Model Fitting Procedure and Model Comparisons. Applications. Univariate Spatial Models for Individual Annual Measures on each Trial. Longitudinal Non-Spatial Models for Several Measures on each Trial. Longitudinal Spatial Models for Repeated Measures on each Trial. Conclusions. Factor Analytic Multiplicative Mixed Models in the Analysis of Multiple Experiments. Introduction. Factor Analytic Models. General Linear Mixed Model and REML Estimation of Factor Analytic, Multivariate and Spatial Models. Constraints and Rotation on Loadings and interpretation of Environmental Loadings and Factorial Scores. Goodness of Fit, Model Comparison and Fitting Procedure. Applications. Eucalypt Data Set. Tea Plant Data Set. Conclusions. Analysis of Interference and Environmental Trend in Field Trials by Joint Modelling of Competition and Spatial Variability. Introduction. Competition Models. Phenotypic Interference. Genotypic Interference. Joint Modelling of Competition Effects and Fertility Trends. Competition Models in Perennial Crops and Forest Trees. Proposed Competition and Spatial Models for Perennial Plants. Competition and Spatial Model ... Mostrar Tudo |
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Palavras-Chave: |
Análiese Estatística - Planta; Análise Multivariada - Panta; Analises estatística; BLUP; Management; Melhoramento genético; Melhoramentp; Method; Métodos; Plant; Planta-melhoramento; Plants; REML; Seleção- método; Selection. |
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Thesagro: |
Análise Estatística; Genética; Melhoramento; Melhoramento Genético Vegetal; Método; Método Estatístico; Planta; Seleção. |
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Thesaurus NAL: |
statistical analysis. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/162207/1/Doc-90.pdf
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Marc: |
LEADER 03481nam a2200445 a 4500
001 1309230
005 2017-07-31
008 2003 bl uuuu 00u1 u #d
022 $a1517-536X
100 1 $aRESENDE, M. D. V. de
245 $aMultivariate spatial statistical analysis of multiple experiments and longitudinal data.
260 $aColombo: Embrapa Florestas$c2003
300 $a126 p.
490 $a(Embrapa Florestas. Documentos, 90).
520 $aMultivariate Spatial Statistical Analysis of Longitudinal Data. Introduction. Description of Models. General Linear Mixed Model and REML Estimation. Univariate Spatial Models for Individual Annual Measures on each Trial. Longitudinal Non-Spatial Models for Several Measures on each Trial. Longitudinal Spatial Models for Repeated Measures on each Trial. Model Fitting Procedure and Model Comparisons. Applications. Univariate Spatial Models for Individual Annual Measures on each Trial. Longitudinal Non-Spatial Models for Several Measures on each Trial. Longitudinal Spatial Models for Repeated Measures on each Trial. Conclusions. Factor Analytic Multiplicative Mixed Models in the Analysis of Multiple Experiments. Introduction. Factor Analytic Models. General Linear Mixed Model and REML Estimation of Factor Analytic, Multivariate and Spatial Models. Constraints and Rotation on Loadings and interpretation of Environmental Loadings and Factorial Scores. Goodness of Fit, Model Comparison and Fitting Procedure. Applications. Eucalypt Data Set. Tea Plant Data Set. Conclusions. Analysis of Interference and Environmental Trend in Field Trials by Joint Modelling of Competition and Spatial Variability. Introduction. Competition Models. Phenotypic Interference. Genotypic Interference. Joint Modelling of Competition Effects and Fertility Trends. Competition Models in Perennial Crops and Forest Trees. Proposed Competition and Spatial Models for Perennial Plants. Competition and Spatial Model for Single Tree Plot Design (Four Neighbours). Competition Model for Single Tree Plot Design (Eight Neighbours). Competition and Spatial Model for Multiple Tree Plot Design (Four Neighbours). Competition and Spatial Model for Multiple Tree Plot Design (Eight Neighbours). Generalised Competition and Spatial Model. Phenotypic Competition and Spatial Model. Missing Plant Effects. Profile Likelihood and Generalisation of REML (GREML). Estimation/Prediction Procedures and Software. Applications to Experimental Data. General Results from Five Different Species. Phenotypic Competition Models via Profile Likelihood in Sugarcane. Genotypic and Phenotypic Competition Models in Eucalyptus maculata. Genotypic and Phenotypic Competition Models in Pinus. Conclusions. References.
650 $astatistical analysis
650 $aAnálise Estatística
650 $aGenética
650 $aMelhoramento
650 $aMelhoramento Genético Vegetal
650 $aMétodo
650 $aMétodo Estatístico
650 $aPlanta
650 $aSeleção
653 $aAnáliese Estatística - Planta
653 $aAnálise Multivariada - Panta
653 $aAnalises estatística
653 $aBLUP
653 $aManagement
653 $aMelhoramento genético
653 $aMelhoramentp
653 $aMethod
653 $aMétodos
653 $aPlant
653 $aPlanta-melhoramento
653 $aPlants
653 $aREML
653 $aSeleção- método
653 $aSelection
700 1 $aTHOMPSON, R.
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Registro original: |
Embrapa Florestas (CNPF) |
