The Experts below are selected from a list of 37203 Experts worldwide ranked by ideXlab platform
Chee Ng - One of the best experts on this subject based on the ideXlab platform.
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a survey of population analysis Methods and software for complex pharmacokinetic and pharmacodynamic models with examples
Aaps Journal, 2007Co-Authors: Robert J Bauer, Serge Guzy, Chee NgAbstract:An overview is provided of the present population analysis Methods and an assessment of which software packages are most appropriate for various PK/PD modeling problems. Four PK/PD example problems were solved using the programs NONMEM VI beta version, PDx-MCPEM, S-ADAPT, MONOLIX, and WinBUGS, informally assessed for reasonable accuracy and stability in analyzing these problems. Also, for each program we describe their general interface, ease of use, and abilities. We conclude with discussing which algorithms and software are most suitable for which types of PK/PD problems. NONMEM FO Method is accurate and fast with 2-compartment models, if intra-individual and interindividual variances are small. The NONMEM FOCE Method is slower than FO, but gives accurate population values regardless of size of intra- and interindividual errors. However, if data are very sparse, the NONMEM FOCE Method can lead to inaccurate values, while the Laplace Method can provide more accurate results. The exact EM Methods (performed using S-ADAPT, PDx-MCPEM, and MONOLIX) have greater stability in analyzing complex PK/PD models, and can provide accurate results with sparse or rich data. MCPEM Methods perform more slowly than NONMEM FOCE for simple models, but perform more quickly and stably than NONMEM FOCE for complex models. WinBUGS provides accurate assessments of the population parameters, standard errors and 95% confidence intervals for all examples. Like the MCPEM Methods, WinBUGS's efficiency increases relative to NONMEM when solving the complex PK/PD models.
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a survey of population analysis Methods and software for complex pharmacokinetic and pharmacodynamic models with examples
Aaps Journal, 2007Co-Authors: Robert J Bauer, Serge Guzy, Chee NgAbstract:An overview is provided of the present population analysis Methods and an assessment of which software packages are most appropriate for various PK/PD modeling problems. Four PK/PD example problems were solved using the programs NONMEM VI beta version, PDx-MCPEM, S-ADAPT, MONOLIX, and WinBUGS, informally assessed for reasonable accuracy and stability in analyzing these problems. Also, for each program we describe their general interface, ease of use, and abilities. We conclude with discussing which algorithms and software are most suitable for which types of PK/PD problems. NONMEM FO Method is accurate and fast with 2-compartment models, if intra-individual and interindividual variances are small. The NONMEM FOCE Method is slower than FO, but gives accurate population values regardless of size of intra- and interindividual errors. However, if data are very sparse, the NONMEM FOCE Method can lead to inaccurate values, while the Laplace Method can provide more accurate results. The exact EM Methods (performed using S-ADAPT, PDx-MCPEM, and MONOLIX) have greater stability in analyzing complex PK/PD models, and can provide accurate results with sparse or rich data. MCPEM Methods perform more slowly than NONMEM FOCE for simple models, but perform more quickly and stably than NONMEM FOCE for complex models. WinBUGS provides accurate assessments of the population parameters, standard errors and 95% confidence intervals for all examples. Like the MCPEM Methods, WinBUGS's efficiency increases relative to NONMEM when solving the complex PK/PD models.
Robert J Bauer - One of the best experts on this subject based on the ideXlab platform.
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a survey of population analysis Methods and software for complex pharmacokinetic and pharmacodynamic models with examples
Aaps Journal, 2007Co-Authors: Robert J Bauer, Serge Guzy, Chee NgAbstract:An overview is provided of the present population analysis Methods and an assessment of which software packages are most appropriate for various PK/PD modeling problems. Four PK/PD example problems were solved using the programs NONMEM VI beta version, PDx-MCPEM, S-ADAPT, MONOLIX, and WinBUGS, informally assessed for reasonable accuracy and stability in analyzing these problems. Also, for each program we describe their general interface, ease of use, and abilities. We conclude with discussing which algorithms and software are most suitable for which types of PK/PD problems. NONMEM FO Method is accurate and fast with 2-compartment models, if intra-individual and interindividual variances are small. The NONMEM FOCE Method is slower than FO, but gives accurate population values regardless of size of intra- and interindividual errors. However, if data are very sparse, the NONMEM FOCE Method can lead to inaccurate values, while the Laplace Method can provide more accurate results. The exact EM Methods (performed using S-ADAPT, PDx-MCPEM, and MONOLIX) have greater stability in analyzing complex PK/PD models, and can provide accurate results with sparse or rich data. MCPEM Methods perform more slowly than NONMEM FOCE for simple models, but perform more quickly and stably than NONMEM FOCE for complex models. WinBUGS provides accurate assessments of the population parameters, standard errors and 95% confidence intervals for all examples. Like the MCPEM Methods, WinBUGS's efficiency increases relative to NONMEM when solving the complex PK/PD models.
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a survey of population analysis Methods and software for complex pharmacokinetic and pharmacodynamic models with examples
Aaps Journal, 2007Co-Authors: Robert J Bauer, Serge Guzy, Chee NgAbstract:An overview is provided of the present population analysis Methods and an assessment of which software packages are most appropriate for various PK/PD modeling problems. Four PK/PD example problems were solved using the programs NONMEM VI beta version, PDx-MCPEM, S-ADAPT, MONOLIX, and WinBUGS, informally assessed for reasonable accuracy and stability in analyzing these problems. Also, for each program we describe their general interface, ease of use, and abilities. We conclude with discussing which algorithms and software are most suitable for which types of PK/PD problems. NONMEM FO Method is accurate and fast with 2-compartment models, if intra-individual and interindividual variances are small. The NONMEM FOCE Method is slower than FO, but gives accurate population values regardless of size of intra- and interindividual errors. However, if data are very sparse, the NONMEM FOCE Method can lead to inaccurate values, while the Laplace Method can provide more accurate results. The exact EM Methods (performed using S-ADAPT, PDx-MCPEM, and MONOLIX) have greater stability in analyzing complex PK/PD models, and can provide accurate results with sparse or rich data. MCPEM Methods perform more slowly than NONMEM FOCE for simple models, but perform more quickly and stably than NONMEM FOCE for complex models. WinBUGS provides accurate assessments of the population parameters, standard errors and 95% confidence intervals for all examples. Like the MCPEM Methods, WinBUGS's efficiency increases relative to NONMEM when solving the complex PK/PD models.
V. R. Fatalov - One of the best experts on this subject based on the ideXlab platform.
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functional integrals for the bogoliubov gaussian measure exact asymptotic forms
Theoretical and Mathematical Physics, 2018Co-Authors: V. R. FatalovAbstract:We prove theorems on the exact asymptotic forms as u → ∞ of two functional integrals over the Bogoliubov measure μB of the forms $$\int_{C[0,\beta ]} {[\int_0^\beta {|x(t){|^p}dt{]^u}d{\mu _B}(x)} } ,\;\int_{C(0,\beta )} {\exp \left\{ {\mu {{(\int_0^\beta {|x(t){|^p}dt} )}^{a/p}}} \right\}d{\mu _B}(x)} $$ for p = 4, 6, 8, 10 with p > p0, where p0 = 2+4π2/β2ω2 is the threshold value, β is the inverse temperature, ω is the eigenfrequency of the harmonic oscillator, and 0 < α < 2. As the Method of study, we use the Laplace Method in Hilbert functional spaces for distributions of almost surely continuous Gaussian processes.
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exact Laplace type asymptotic formulas for the bogoliubov gaussian measure the set of minimum points of the action functional
Theoretical and Mathematical Physics, 2017Co-Authors: V. R. FatalovAbstract:We prove a theorem on the exact asymptotic relations of large deviations of the Bogoliubov measure in the L p norm for p = 4, 6, 8, 10 with p > p 0, where p 0 = 2+4π 2/β 2 ω 2 is a threshold value, β > 0 is the inverse temperature, and ω > 0 is the natural frequency of the harmonic oscillator. For the study, we use the Laplace Method in function spaces for Gaussian measures.
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Perturbation theory series in quantum mechanics: Phase transition and exact asymptotic forms for the expansion coefficients
Theoretical and Mathematical Physics, 2013Co-Authors: V. R. FatalovAbstract:We consider the model of a harmonic oscillator with a power-law potential and derive new asymptotic formulas for the coefficients of the perturbation theory series in powers of the coupling constant in the case of a power-law perturbing potential |x|p, p > 0. We prove the existence of a critical value p0 and compute it. It is a threshold in the sense that the asymptotic forms of the studied coefficients for 0 p0 differ qualitatively. We note that the considered physical system undergoes a phase transition at p = p0. The analysis uses the Laplace Method for functional integrals with Gaussian measures.
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integral functionals for the exponential of the wiener process and the brownian bridge exact asymptotics and legendre functions
Mathematical Notes, 2012Co-Authors: V. R. FatalovAbstract:We prove results concerning the exact asymptotics of the probabilities $$P\left\{ {\int_0^1 {e^{\varepsilon \xi (t)} dt < b} } \right\}, P\left\{ {\int_0^1 {e^{\varepsilon \left| {\xi (t)} \right|} dt < b} } \right\}$$ as ɛ → 0 and 0 < b < 1 for two Gaussian processes ξ(t), the Wiener process and the Brownian bridge. We also obtain asymptotic formulas for integrals of Laplace type. Our study is based on the Laplace Method for Gaussian measures in Banach spaces. The calculations of the constants are reduced to the solution of an extremal problem for the action functional and to the study of the spectrum of a second-order differential operator of Sturm-Liouville type using the Legendre functions.
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exact asymptotics of distributions of integral functionals of the geometric brownian motion and other related formulas
Problems of Information Transmission, 2007Co-Authors: V. R. FatalovAbstract:We prove results on exact asymptotics of the probabilities $$P\left\{ {\int\limits_0^1 {e^{\varepsilon \xi (t)} dt > b} } \right\},P\left\{ {\int\limits_0^1 {e^{\varepsilon |\xi (t)|} dt > b} } \right\},\varepsilon \to 0,$$ where b > 1, for two Gaussian processes ?(t), namely, a Wiener process and a Brownian bridge. We use the Laplace Method for Gaussian measures in Banach spaces. Evaluation of constants is reduced to solving an extreme value problem for the rate function and studying the spectrum of a second-order differential operator of the Sturm-Liouville type with the use of Legendre functions.
Serge Guzy - One of the best experts on this subject based on the ideXlab platform.
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a survey of population analysis Methods and software for complex pharmacokinetic and pharmacodynamic models with examples
Aaps Journal, 2007Co-Authors: Robert J Bauer, Serge Guzy, Chee NgAbstract:An overview is provided of the present population analysis Methods and an assessment of which software packages are most appropriate for various PK/PD modeling problems. Four PK/PD example problems were solved using the programs NONMEM VI beta version, PDx-MCPEM, S-ADAPT, MONOLIX, and WinBUGS, informally assessed for reasonable accuracy and stability in analyzing these problems. Also, for each program we describe their general interface, ease of use, and abilities. We conclude with discussing which algorithms and software are most suitable for which types of PK/PD problems. NONMEM FO Method is accurate and fast with 2-compartment models, if intra-individual and interindividual variances are small. The NONMEM FOCE Method is slower than FO, but gives accurate population values regardless of size of intra- and interindividual errors. However, if data are very sparse, the NONMEM FOCE Method can lead to inaccurate values, while the Laplace Method can provide more accurate results. The exact EM Methods (performed using S-ADAPT, PDx-MCPEM, and MONOLIX) have greater stability in analyzing complex PK/PD models, and can provide accurate results with sparse or rich data. MCPEM Methods perform more slowly than NONMEM FOCE for simple models, but perform more quickly and stably than NONMEM FOCE for complex models. WinBUGS provides accurate assessments of the population parameters, standard errors and 95% confidence intervals for all examples. Like the MCPEM Methods, WinBUGS's efficiency increases relative to NONMEM when solving the complex PK/PD models.
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a survey of population analysis Methods and software for complex pharmacokinetic and pharmacodynamic models with examples
Aaps Journal, 2007Co-Authors: Robert J Bauer, Serge Guzy, Chee NgAbstract:An overview is provided of the present population analysis Methods and an assessment of which software packages are most appropriate for various PK/PD modeling problems. Four PK/PD example problems were solved using the programs NONMEM VI beta version, PDx-MCPEM, S-ADAPT, MONOLIX, and WinBUGS, informally assessed for reasonable accuracy and stability in analyzing these problems. Also, for each program we describe their general interface, ease of use, and abilities. We conclude with discussing which algorithms and software are most suitable for which types of PK/PD problems. NONMEM FO Method is accurate and fast with 2-compartment models, if intra-individual and interindividual variances are small. The NONMEM FOCE Method is slower than FO, but gives accurate population values regardless of size of intra- and interindividual errors. However, if data are very sparse, the NONMEM FOCE Method can lead to inaccurate values, while the Laplace Method can provide more accurate results. The exact EM Methods (performed using S-ADAPT, PDx-MCPEM, and MONOLIX) have greater stability in analyzing complex PK/PD models, and can provide accurate results with sparse or rich data. MCPEM Methods perform more slowly than NONMEM FOCE for simple models, but perform more quickly and stably than NONMEM FOCE for complex models. WinBUGS provides accurate assessments of the population parameters, standard errors and 95% confidence intervals for all examples. Like the MCPEM Methods, WinBUGS's efficiency increases relative to NONMEM when solving the complex PK/PD models.
Emmanuel Lesaffre - One of the best experts on this subject based on the ideXlab platform.
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fully exponential Laplace approximations for the joint modelling of survival and longitudinal data
Journal of The Royal Statistical Society Series B-statistical Methodology, 2009Co-Authors: Dimitris Rizopoulos, Geert Verbeke, Emmanuel LesaffreAbstract:Summary. A common objective in longitudinal studies is the joint modelling of a longitudinal response with a time‐to‐event outcome. Random effects are typically used in the joint modelling framework to explain the interrelationships between these two processes. However, estimation in the presence of random effects involves intractable integrals requiring numerical integration. We propose a new computational approach for fitting such models that is based on the Laplace Method for integrals that makes the consideration of high dimensional random‐effects structures feasible. Contrary to the standard Laplace approximation, our Method requires much fewer repeated measurements per individual to produce reliable results.
