http://dbpedia.org/ontology/abstract
|
Nonlinear mixed-effects models are a speci … Nonlinear mixed-effects models are a special case of regression analysis for which a range of different software solutions are available. The statistical properties of nonlinear mixed-effects models make direct estimation by a BLUE estimator impossible. Nonlinear mixed effects models are therefore estimated according to Maximum Likelihood principles. Specific estimation methods are applied, such as linearization methods as first-order (FO), first-order conditional (FOCE) or the laplacian (LAPL), approximation methods such as iterative-two stage (ITS), importance sampling (IMP), stochastic approximation estimation (SAEM) or direct sampling. A special case is use of non-parametric approaches. Furthermore, estimation in limited or full Bayesian frameworks is performed using the Metropolis-Hastings or the NUTS algorithms. Some software solutions focus on a single estimation method, others cover a range of estimation methods and/or with interfaces for specific use cases.or with interfaces for specific use cases.
|
http://dbpedia.org/ontology/wikiPageID
|
70739538
|
http://dbpedia.org/ontology/wikiPageLength
|
6209
|
http://dbpedia.org/ontology/wikiPageRevisionID
|
1097249378
|
http://dbpedia.org/ontology/wikiPageWikiLink
|
http://dbpedia.org/resource/Stan_%28software%29 +
, http://dbpedia.org/resource/Software +
, http://dbpedia.org/resource/Runge%E2%80%93Kutta_methods +
, http://dbpedia.org/resource/Metropolis%E2%80%93Hastings_algorithm +
, http://dbpedia.org/resource/SAS_%28software%29 +
, http://dbpedia.org/resource/R_%28programming_language%29 +
, http://dbpedia.org/resource/Gauss%E2%80%93Markov_theorem +
, http://dbpedia.org/resource/Pharmacometrics +
, http://dbpedia.org/resource/Category:Numerical_software +
, http://dbpedia.org/resource/WinBUGS +
, http://dbpedia.org/resource/Nonlinear_mixed-effects_model +
, http://dbpedia.org/resource/SPSS +
, http://dbpedia.org/resource/NONMEM +
, http://dbpedia.org/resource/Optimal_design +
, http://dbpedia.org/resource/LAPACK +
, http://dbpedia.org/resource/Maximum_Likelihood +
, http://dbpedia.org/resource/Hamiltonian_Monte_Carlo +
, http://dbpedia.org/resource/Julia_%28programming_language%29 +
, http://dbpedia.org/resource/Category:Regression_analysis +
, http://dbpedia.org/resource/Bayesian +
, http://dbpedia.org/resource/Regression_analysis +
, http://dbpedia.org/resource/MATLAB +
, http://dbpedia.org/resource/Physiologically_based_pharmacokinetic_modelling +
, http://dbpedia.org/resource/Ordinary_differential_equation +
|
http://dbpedia.org/property/wikiPageUsesTemplate
|
http://dbpedia.org/resource/Template:Short_description +
, http://dbpedia.org/resource/Template:Reflist +
|
http://purl.org/dc/terms/subject
|
http://dbpedia.org/resource/Category:Regression_analysis +
, http://dbpedia.org/resource/Category:Numerical_software +
|
http://www.w3.org/ns/prov#wasDerivedFrom
|
http://en.wikipedia.org/wiki/Non-linear_mixed-effects_modeling_software?oldid=1097249378&ns=0 +
|
http://xmlns.com/foaf/0.1/isPrimaryTopicOf
|
http://en.wikipedia.org/wiki/Non-linear_mixed-effects_modeling_software +
|
owl:sameAs |
http://dbpedia.org/resource/Non-linear_mixed-effects_modeling_software +
, https://global.dbpedia.org/id/GUwku +
, http://www.wikidata.org/entity/Q112119093 +
|
rdfs:comment |
Nonlinear mixed-effects models are a speci … Nonlinear mixed-effects models are a special case of regression analysis for which a range of different software solutions are available. The statistical properties of nonlinear mixed-effects models make direct estimation by a BLUE estimator impossible. Nonlinear mixed effects models are therefore estimated according to Maximum Likelihood principles. Specific estimation methods are applied, such as linearization methods as first-order (FO), first-order conditional (FOCE) or the laplacian (LAPL), approximation methods such as iterative-two stage (ITS), importance sampling (IMP), stochastic approximation estimation (SAEM) or direct sampling. A special case is use of non-parametric approaches. Furthermore, estimation in limited or full Bayesian frameworks is performed using the Metropolis-Hasorks is performed using the Metropolis-Has
|
rdfs:label |
Non-linear mixed-effects modeling software
|