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You searched for subject:( Concordance model). Showing records 1 – 4 of 4 total matches.

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University of Akron

1. Chandler, Megan M. Examining the Mechanisisms by which Situational and Individual Difference Variables Relate to Workplace Deviance: The Mediating Role of Goal Self-Concordance.

Degree: MA, Psychology, 2008, University of Akron

 The purpose of this study was to examine whether variables derived from the self-concordance model mediate the influence of individual and situational variables on workplace… (more)

Subjects/Keywords: Psychology; Self-Concordance Model; Workplace Deviance

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Chandler, M. M. (2008). Examining the Mechanisisms by which Situational and Individual Difference Variables Relate to Workplace Deviance: The Mediating Role of Goal Self-Concordance. (Masters Thesis). University of Akron. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=akron1216846236

Chicago Manual of Style (16th Edition):

Chandler, Megan M. “Examining the Mechanisisms by which Situational and Individual Difference Variables Relate to Workplace Deviance: The Mediating Role of Goal Self-Concordance.” 2008. Masters Thesis, University of Akron. Accessed October 14, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1216846236.

MLA Handbook (7th Edition):

Chandler, Megan M. “Examining the Mechanisisms by which Situational and Individual Difference Variables Relate to Workplace Deviance: The Mediating Role of Goal Self-Concordance.” 2008. Web. 14 Oct 2019.

Vancouver:

Chandler MM. Examining the Mechanisisms by which Situational and Individual Difference Variables Relate to Workplace Deviance: The Mediating Role of Goal Self-Concordance. [Internet] [Masters thesis]. University of Akron; 2008. [cited 2019 Oct 14]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1216846236.

Council of Science Editors:

Chandler MM. Examining the Mechanisisms by which Situational and Individual Difference Variables Relate to Workplace Deviance: The Mediating Role of Goal Self-Concordance. [Masters Thesis]. University of Akron; 2008. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=akron1216846236


The Ohio State University

2. Yu, Li. Tau-Path Test - A Nonparametric Test For Testing Unspecified Subpopulation Monotone Association.

Degree: PhD, Statistics, 2009, The Ohio State University

 In data mining and other settings, there is sometimes a need to identify relationships between variables when the relationship may hold only over a subset… (more)

Subjects/Keywords: Statistics; Concordance matrix; copula; drug assay; microarray; mixture; permutation; quassinoids; bivariate; Mallow's model; multistage

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APA (6th Edition):

Yu, L. (2009). Tau-Path Test - A Nonparametric Test For Testing Unspecified Subpopulation Monotone Association. (Doctoral Dissertation). The Ohio State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=osu1255657068

Chicago Manual of Style (16th Edition):

Yu, Li. “Tau-Path Test - A Nonparametric Test For Testing Unspecified Subpopulation Monotone Association.” 2009. Doctoral Dissertation, The Ohio State University. Accessed October 14, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1255657068.

MLA Handbook (7th Edition):

Yu, Li. “Tau-Path Test - A Nonparametric Test For Testing Unspecified Subpopulation Monotone Association.” 2009. Web. 14 Oct 2019.

Vancouver:

Yu L. Tau-Path Test - A Nonparametric Test For Testing Unspecified Subpopulation Monotone Association. [Internet] [Doctoral dissertation]. The Ohio State University; 2009. [cited 2019 Oct 14]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1255657068.

Council of Science Editors:

Yu L. Tau-Path Test - A Nonparametric Test For Testing Unspecified Subpopulation Monotone Association. [Doctoral Dissertation]. The Ohio State University; 2009. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=osu1255657068


University of Cambridge

3. Hee, Sonke. Computational Bayesian techniques applied to cosmology.

Degree: PhD, 2018, University of Cambridge

 This thesis presents work around 3 themes: dark energy, gravitational waves and Bayesian inference. Both dark energy and gravitational wave physics are not yet well… (more)

Subjects/Keywords: Bayesian inference; Cosmology; Dark Energy; LCDM; Quintessence; Statistics; Gravitational waves; Tests of GR; Computational acceleration; Nested Sampling; General Relativity; Multinest; PolyChord; Product Space MCMC; Model selection; Posterior odds; Posterior Odds Ratio; Bayes factors; Parameter estimation; Equation of state; Phantom Dark Energy; Microwave background radiation; CMB; Supernovae; Baryonic Acoustic Oscillations; Data constraints; Kullback Leibler Divergence; KL divergence; LIGO; Constraining power; Lyman alpha forest; Bayesian; Bayes theorem; Probability; Efficiency; Concordance model; Parameter reconstruction; Marginal Likelihood; Kerr waveform; Free-form reconstruction; w(z); w=-1; Cosmological constant; Model comparison; Evidence; CosmoMC; CAMB; Hyper-likelihood; Model averaging; Planck

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hee, S. (2018). Computational Bayesian techniques applied to cosmology. (Doctoral Dissertation). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/273346 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744549

Chicago Manual of Style (16th Edition):

Hee, Sonke. “Computational Bayesian techniques applied to cosmology.” 2018. Doctoral Dissertation, University of Cambridge. Accessed October 14, 2019. https://www.repository.cam.ac.uk/handle/1810/273346 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744549.

MLA Handbook (7th Edition):

Hee, Sonke. “Computational Bayesian techniques applied to cosmology.” 2018. Web. 14 Oct 2019.

Vancouver:

Hee S. Computational Bayesian techniques applied to cosmology. [Internet] [Doctoral dissertation]. University of Cambridge; 2018. [cited 2019 Oct 14]. Available from: https://www.repository.cam.ac.uk/handle/1810/273346 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744549.

Council of Science Editors:

Hee S. Computational Bayesian techniques applied to cosmology. [Doctoral Dissertation]. University of Cambridge; 2018. Available from: https://www.repository.cam.ac.uk/handle/1810/273346 ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.744549


University of Cambridge

4. Hee, Sonke. Computational Bayesian techniques applied to cosmology .

Degree: 2018, University of Cambridge

 This thesis presents work around 3 themes: dark energy, gravitational waves and Bayesian inference. Both dark energy and gravitational wave physics are not yet well… (more)

Subjects/Keywords: Bayesian inference; Cosmology; Dark Energy; LCDM; Quintessence; Statistics; Gravitational waves; Tests of GR; Computational acceleration; Nested Sampling; General Relativity; Multinest; PolyChord; Product Space MCMC; Model selection; Posterior odds; Posterior Odds Ratio; Bayes factors; Parameter estimation; Equation of state; Phantom Dark Energy; Microwave background radiation; CMB; Supernovae; Baryonic Acoustic Oscillations; Data constraints; Kullback Leibler Divergence; KL divergence; LIGO; Constraining power; Lyman alpha forest; Bayesian; Bayes theorem; Probability; Efficiency; Concordance model; Parameter reconstruction; Marginal Likelihood; Kerr waveform; Free-form reconstruction; w(z); w=-1; Cosmological constant; Model comparison; Evidence; CosmoMC; CAMB; Hyper-likelihood; Model averaging; Planck

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Hee, S. (2018). Computational Bayesian techniques applied to cosmology . (Thesis). University of Cambridge. Retrieved from https://www.repository.cam.ac.uk/handle/1810/273346

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Hee, Sonke. “Computational Bayesian techniques applied to cosmology .” 2018. Thesis, University of Cambridge. Accessed October 14, 2019. https://www.repository.cam.ac.uk/handle/1810/273346.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Hee, Sonke. “Computational Bayesian techniques applied to cosmology .” 2018. Web. 14 Oct 2019.

Vancouver:

Hee S. Computational Bayesian techniques applied to cosmology . [Internet] [Thesis]. University of Cambridge; 2018. [cited 2019 Oct 14]. Available from: https://www.repository.cam.ac.uk/handle/1810/273346.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Hee S. Computational Bayesian techniques applied to cosmology . [Thesis]. University of Cambridge; 2018. Available from: https://www.repository.cam.ac.uk/handle/1810/273346

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.