The Experts below are selected from a list of 562992 Experts worldwide ranked by ideXlab platform

X. Aymerich - One of the best experts on this subject based on the ideXlab platform.

  • A function-Fit Model for the soft breakdown failure mode
    IEEE Electron Device Letters, 1999
    Co-Authors: Enrique Miranda, Jordi Suñé, Rosana Rodriguez, Montserrat Nafria, X. Aymerich
    Abstract:

    An empirical one parameter-based power law Model for the leakage current through one or more soft breakdown spots in ultrathin (

  • a function Fit Model for the soft breakdown failure mode
    IEEE Electron Device Letters, 1999
    Co-Authors: E Miranda, Rosana Rodriguez, Montserrat Nafria, J Sune, X. Aymerich
    Abstract:

    An empirical one parameter-based power law Model for the leakage current through one or more soft breakdown spots in ultrathin (<5 nm) gate oxides is presented. Good Fit to data can be obtained in nearly five decades of current from 0.5 to 5 V. In addition, it is shown that there exists a slight correlation between the parameters which describe the soft breakdown conduction characteristic and the stressing condition which triggers it.

David Posada - One of the best experts on this subject based on the ideXlab platform.

  • prottest selection of best Fit Models of protein evolution
    Bioinformatics, 2005
    Co-Authors: Federico Abascal, Rafael Zardoya, David Posada
    Abstract:

    Summary: Using an appropriate Model of amino acid replacement is very important for the study of protein evolution and phylogenetic inference. We have built a tool for the selection of the best-Fit Model of evolution, among a set of candidate Models, for a given protein sequence alignment. Availability: ProtTest is available under the GNU license from http://darwin.uvigo.es Contact: fabascal@uvigo.es

  • using Modeltest and paup to select a Model of nucleotide substitution
    Current protocols in human genetics, 2003
    Co-Authors: David Posada
    Abstract:

    : Models of nucleotide substitution are commonly used in the analysis of DNA sequences. This unit describes the use of the program ModelTEST (coupled with PAUP*) to find the best-Fit Model of substitution for the sequence alignment at hand. An example data file is analyzed and the interpretation of the results is discussed. Some background theory on Model selection and a discussion of the relevance of Models is included at the end of the unit.

  • selecting the best Fit Model of nucleotide substitution
    Systematic Biology, 2001
    Co-Authors: David Posada, Keith A Crandall
    Abstract:

    Despite the relevant role of Models of nucleotide substitution in phylogenetics, choosing among different Models remains a problem. Several statistical methods for selecting the Model that best Fits the data at hand have been proposed, but their absolute and relative performance has not yet been characterized. In this study, we compare under various conditions the performance of different hierarchical and dynamic likelihood ratio tests, and of Akaike and Bayesian information methods, for selecting best-Fit Models of nucleotide substitution. We specifically examine the role of the topology used to estimate the likelihood of the different Models and the importance of the order in which hypotheses are tested. We do this by simulating DNA sequences under a known Model of nucleotide substitution and recording how often this true Model is recovered by the different methods. Our results suggest that Model selection is reasonably accurate and indicate that some likelihood ratio test methods perform overall better than the Akaike or Bayesian information criteria. The tree used to estimate the likelihood scores does not influence Model selection unless it is a randomly chosen tree. The order in which hypotheses are tested, and the complexity of the initial Model in the sequence of tests, influence Model selection in some cases. Model Fitting in phylogenetics has been suggested for many years, yet many authors still arbitrarily choose their Models, often using the default Models implemented in standard computer programs for phylogenetic estimation. We show here that a best-Fit Model can be readily identified. Consequently, given the relevance of Models, Model Fitting should be routine in any phylogenetic analysis that uses Models of evolution.

  • selecting the best Fit Model of nucleotide substitution
    Systematic Biology, 2001
    Co-Authors: David Posada, Keith A Crandall
    Abstract:

    Despite the relevant role of Models of nucleotide substitution in phylogenetics, choosing among different Models remains a problem. Several statistical methods for selecting the Model that best ets the data at hand have been proposed, but their absolute and relative performance has not yet been characterized. In this study, we compare under various conditions the performance of different hierarchicaland dynamic likelihood ratio tests, and of Akaikeand Bayesian information methods, for selecting best-et Models of nucleotide substitution. We speciecally examine the role of the topology used to estimate the likelihood of the different Models and the importance of the order in which hypotheses are tested. We do this by simulating DNA sequences under a known Model of nucleotide substitutionandrecordinghowoftenthistrueModelisrecoveredbythedifferentmethods.Ourresults suggestthatModelselectionisreasonablyaccurateandindicatethatsomelikelihoodratiotestmethods perform overall better than the Akaike or Bayesian information criteria. The tree used to estimate the likelihood scores does not ineuence Model selection unless it is a randomly chosen tree. The order in which hypothesesare tested,and the complexity of theinitialModelinthe sequence oftests, ineuence Model selection in some cases. Model etting in phylogenetics has been suggested for many years, yet many authors still arbitrarily choose their Models, often using the default Models implemented in standard computer programs for phylogenetic estimation. We show here that a best-et Model can be readily identieed. Consequently, given the relevance of Models, Model etting should be routine in any phylogenetic analysis that uses Models of evolution. (AIC; BIC; dynamic LRT; hierarchical LRT; likelihood ratio tests; Model selection; substitution Models.)

E Miranda - One of the best experts on this subject based on the ideXlab platform.

  • a function Fit Model for the soft breakdown failure mode
    IEEE Electron Device Letters, 1999
    Co-Authors: E Miranda, Rosana Rodriguez, Montserrat Nafria, J Sune, X. Aymerich
    Abstract:

    An empirical one parameter-based power law Model for the leakage current through one or more soft breakdown spots in ultrathin (<5 nm) gate oxides is presented. Good Fit to data can be obtained in nearly five decades of current from 0.5 to 5 V. In addition, it is shown that there exists a slight correlation between the parameters which describe the soft breakdown conduction characteristic and the stressing condition which triggers it.

Keith A Crandall - One of the best experts on this subject based on the ideXlab platform.

  • selecting the best Fit Model of nucleotide substitution
    Systematic Biology, 2001
    Co-Authors: David Posada, Keith A Crandall
    Abstract:

    Despite the relevant role of Models of nucleotide substitution in phylogenetics, choosing among different Models remains a problem. Several statistical methods for selecting the Model that best Fits the data at hand have been proposed, but their absolute and relative performance has not yet been characterized. In this study, we compare under various conditions the performance of different hierarchical and dynamic likelihood ratio tests, and of Akaike and Bayesian information methods, for selecting best-Fit Models of nucleotide substitution. We specifically examine the role of the topology used to estimate the likelihood of the different Models and the importance of the order in which hypotheses are tested. We do this by simulating DNA sequences under a known Model of nucleotide substitution and recording how often this true Model is recovered by the different methods. Our results suggest that Model selection is reasonably accurate and indicate that some likelihood ratio test methods perform overall better than the Akaike or Bayesian information criteria. The tree used to estimate the likelihood scores does not influence Model selection unless it is a randomly chosen tree. The order in which hypotheses are tested, and the complexity of the initial Model in the sequence of tests, influence Model selection in some cases. Model Fitting in phylogenetics has been suggested for many years, yet many authors still arbitrarily choose their Models, often using the default Models implemented in standard computer programs for phylogenetic estimation. We show here that a best-Fit Model can be readily identified. Consequently, given the relevance of Models, Model Fitting should be routine in any phylogenetic analysis that uses Models of evolution.

  • selecting the best Fit Model of nucleotide substitution
    Systematic Biology, 2001
    Co-Authors: David Posada, Keith A Crandall
    Abstract:

    Despite the relevant role of Models of nucleotide substitution in phylogenetics, choosing among different Models remains a problem. Several statistical methods for selecting the Model that best ets the data at hand have been proposed, but their absolute and relative performance has not yet been characterized. In this study, we compare under various conditions the performance of different hierarchicaland dynamic likelihood ratio tests, and of Akaikeand Bayesian information methods, for selecting best-et Models of nucleotide substitution. We speciecally examine the role of the topology used to estimate the likelihood of the different Models and the importance of the order in which hypotheses are tested. We do this by simulating DNA sequences under a known Model of nucleotide substitutionandrecordinghowoftenthistrueModelisrecoveredbythedifferentmethods.Ourresults suggestthatModelselectionisreasonablyaccurateandindicatethatsomelikelihoodratiotestmethods perform overall better than the Akaike or Bayesian information criteria. The tree used to estimate the likelihood scores does not ineuence Model selection unless it is a randomly chosen tree. The order in which hypothesesare tested,and the complexity of theinitialModelinthe sequence oftests, ineuence Model selection in some cases. Model etting in phylogenetics has been suggested for many years, yet many authors still arbitrarily choose their Models, often using the default Models implemented in standard computer programs for phylogenetic estimation. We show here that a best-et Model can be readily identieed. Consequently, given the relevance of Models, Model etting should be routine in any phylogenetic analysis that uses Models of evolution. (AIC; BIC; dynamic LRT; hierarchical LRT; likelihood ratio tests; Model selection; substitution Models.)

Rosana Rodriguez - One of the best experts on this subject based on the ideXlab platform.

  • A function-Fit Model for the soft breakdown failure mode
    IEEE Electron Device Letters, 1999
    Co-Authors: Enrique Miranda, Jordi Suñé, Rosana Rodriguez, Montserrat Nafria, X. Aymerich
    Abstract:

    An empirical one parameter-based power law Model for the leakage current through one or more soft breakdown spots in ultrathin (

  • a function Fit Model for the soft breakdown failure mode
    IEEE Electron Device Letters, 1999
    Co-Authors: E Miranda, Rosana Rodriguez, Montserrat Nafria, J Sune, X. Aymerich
    Abstract:

    An empirical one parameter-based power law Model for the leakage current through one or more soft breakdown spots in ultrathin (<5 nm) gate oxides is presented. Good Fit to data can be obtained in nearly five decades of current from 0.5 to 5 V. In addition, it is shown that there exists a slight correlation between the parameters which describe the soft breakdown conduction characteristic and the stressing condition which triggers it.