| 1. |
- Mobasher, B., et al.
(författare)
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Photometric redshifts of galaxies in COSMOS
- 2007
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Ingår i: Astrophysical Journal Supplement Series. - : American Astronomical Society. - 0067-0049 .- 1538-4365. ; 172:1, s. 117-131
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Tidskriftsartikel (refereegranskat)abstract
- We present photometric redshifts for the COSMOS survey derived from a new code, optimized to yield accurate and reliable redshifts and spectral types of galaxies down to faint magnitudes and redshifts out to z similar to 1.2. The technique uses chi (2) template fitting, combined with luminosity function priors and with the option to estimate the internal extinction [ or E( B-V)]. The median most probable redshift, best-fit spectral type and reddening, absolute magnitude, and stellarmass are derived in addition to the full redshift probability distributions. Using simulations with sampling and noise similar to those in COSMOS, the accuracy and reliability is estimated for the photometric redshifts as a function of the magnitude limits of the sample, S/N ratios, and the number of bands used. We find from the simulations that the ratio of derived 95% confidence interval in the chi (2) probability distribution to the estimated photometric redshift (D-95) can be used to identify and exclude the catastrophic failures in the photometric redshift estimates. To evaluate the reliability of the photometric redshifts, we compare the derived redshifts with high-reliability spectroscopic redshifts for a sample of 868 normal galaxies with z < 1: 2 from zCOSMOS. Considering different scenarios, depending on using prior, no prior, and/or extinction, we compare the photometric and spectroscopic redshifts for this sample. The rms scatter between the estimated photometric redshifts and known spectroscopic redshifts is sigma(Delta( z))= 0. 031, where Delta(z) ( z(phot) - z(spec))/( 1+ z(spec)) with a small fraction of outliers (< 2.5%) [ outliers are defined as objects with Delta( z) > 3 sigma(Delta( z)), where sigma(Delta(z)) is the rms scatter in Delta( z)]. We also find good agreement [sigma(Delta(z))= 0.10] between photometric and spectroscopic redshifts for type II AGNs. We compare results fromour photometric redshift procedure with three other independent codes and find them in excellent agreement. We show preliminary results, based on photometric redshifts for the entire COSMOS sample ( to i < 25 mag).
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| 2. |
- Nguyen, T. H. T., et al.
(författare)
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Model Evaluation of Continuous Data Pharmacometric Models : Metrics and Graphics
- 2017
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Ingår i: CPT. - : WILEY. - 2163-8306. ; 6:2, s. 87-109
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Tidskriftsartikel (refereegranskat)abstract
- This article represents the first in a series of tutorials on model evaluation in nonlinear mixed effect models (NLMEMs), from the International Society of Pharmacometrics (ISoP) Model Evaluation Group. Numerous tools are available for evaluation of NLMEM, with a particular emphasis on visual assessment. This first basic tutorial focuses on presenting graphical evaluation tools of NLMEM for continuous data. It illustrates graphs for correct or misspecified models, discusses their pros and cons, and recalls the definition of metrics used.
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| 3. |
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| 4. |
- Venkatakrishnan, K., et al.
(författare)
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Optimizing Oncology Therapeutics Through Quantitative Translational and Clinical Pharmacology : Challenges and Opportunities
- 2015
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Ingår i: Clinical Pharmacology and Therapeutics. - : Wiley. - 0009-9236 .- 1532-6535. ; 97:1, s. 37-54
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Tidskriftsartikel (refereegranskat)abstract
- Despite advances in biomedical research that have deepened our understanding of cancer hallmarks, resulting in the discovery and development of targeted therapies, the success rates of oncology drug development remain low. Opportunities remain for objective dose selection informed by exposure-response understanding to optimize the benefit-risk balance of novel therapies for cancer patients. This review article discusses the principles and applications of modeling and simulation approaches across the lifecycle of development of oncology therapeutics. Illustrative examples are used to convey the value gained from integration of quantitative clinical pharmacology strategies from the preclinical-translational phase through confirmatory clinical evaluation of efficacy and safety.
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