The Experts below are selected from a list of 31347 Experts worldwide ranked by ideXlab platform
Shouzhuo Yao - One of the best experts on this subject based on the ideXlab platform.
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surface acoustic wave saw impedance sensor for kinetic assay of trypsin
Microchemical Journal, 1997Co-Authors: Qingyun Cai, Lihua Nie, Ronghui Wang, Shouzhuo YaoAbstract:Abstract The trypsin-catalyzed hydrolysis of benzoyl- l -arginine ethyl ester (BAEE) has been studied systematically at pH 7.8 and 32°C with a Nonlinear Regression Model. The Michaelis constants covering the range from pH 7.0 to 8.6 were determined. The concentrations of enzyme isolated from pig pancreas were determined using the SAW-impedance sensor and the spectrophotometry, respectively. The experimental detection limit of trypsin was 0.3 mU/ml 2 and the recovery of the sensor system ranged from 94.7 to 105% (n= 6). The effects of temperature, pH, and some metal ions on the trypsin activity were investigated.
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a Nonlinear Regression Model applied to kinetic studies of ester hydrolysis with a surface acoustic wave sensor
Talanta, 1996Co-Authors: Quingyun Cai, Ronhgui Wang, Lihua Nie, Shouzhuo YaoAbstract:Abstract A non-linear Regression Model was derived for the simultaneous determination of the rate constant in alkaline hydrolysis of esters and the initial concentration of esters based on the linear relationship between the frequency response of the surface acoustic wave sensor system and the conductivity of the solution. The Model was tested theoretically and experimentally with the methyl-, ethyl-, and n -propyl-acetate systems. The corresponding rate constants estimated at 25 °C are 0.147, 0.103 and 0.0671 respectively.
Martin A Tanner - One of the best experts on this subject based on the ideXlab platform.
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facilitating the gibbs sampler the gibbs stopper and the griddy gibbs sampler
Journal of the American Statistical Association, 1992Co-Authors: Christian Ritter, Martin A TannerAbstract:Abstract The article briefly reviews the history, literature, and form of the Gibbs sampler. An importance sampling device is proposed for converting the output of the Gibbs sampler to a sample from the exact posterior. This Gibbs stopper technique is also useful for assessing convergence of the Gibbs sampler for moderate sized problems. Also presented is an approach for implementing the Gibbs sampler in nonconjugate situations. The basic idea is to approximate the true cdf of each conditional distribution by a piecewise linear function and then sample from the approximation. Questions relating to the number of nodes in the approximation, gap size between successive nodes, and the treatment of unbounded intervals for a given conditional are discussed. The methodology is illustrated using a genetic linkage Model, a Nonlinear Regression Model, and the Cox Model.
Wenzhi Yang - One of the best experts on this subject based on the ideXlab platform.
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large deviation for a least squares estimator in a Nonlinear Regression Model
Statistics & Probability Letters, 2014Co-Authors: Wenzhi YangAbstract:Abstract By using a large deviation theory of the stochastic process and the moment information of errors, some large deviation results for the least squares estimator θ n in a Nonlinear Regression Model are obtained when errors satisfy some general conditions. For some p > 1 , examples are presented to show that our results can be used in the case for sup n ≥ 1 E | ξ n | p = ∞ and a better bound can be obtained in the case for sup n ≥ 1 E | ξ n | p ∞ . Our results generalize and improve the corresponding ones.
Kyung Ha Seok - One of the best experts on this subject based on the ideXlab platform.
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hybrid fuzzy least squares support vector machine Regression for crisp input and fuzzy output
Communications for Statistical Applications and Methods, 2010Co-Authors: Jooyong Shim, Kyung Ha Seok, Changha HwangAbstract:Hybrid fuzzy Regression analysis is used for integrating randomness and fuzziness into a Regression Model. Least squares support vector machine(LS-SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate hybrid fuzzy linear and Nonlinear Regression Models with crisp inputs and fuzzy output using weighted fuzzy arithmetic(WFA) and LS-SVM. LS-SVM allows us to perform fuzzy Nonlinear Regression analysis by constructing a fuzzy linear Regression function in a high dimensional feature space. The proposed method is not computationally expensive since its solution is obtained from a simple linear equation system. In particular, this method is a very attractive approach to Modeling Nonlinear data, and is nonparametric method in the sense that we do not have to assume the underlying Model function for fuzzy Nonlinear Regression Model with crisp inputs and fuzzy output. Experimental results are then presented which indicate the performance of this method.
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support vector interval Regression machine for crisp input and output data
Fuzzy Sets and Systems, 2006Co-Authors: Changha Hwang, Dug Hun Hong, Kyung Ha SeokAbstract:Support vector Regression (SVR) has been very successful in function estimation problems for crisp data. In this paper, we propose a robust method to evaluate interval Regression Models for crisp input and output data combining the possibility estimation formulation integrating the property of central tendency with the principle of standard SVR. The proposed method is robust in the sense that outliers do not affect the resulting interval Regression. Furthermore, the proposed method is Model-free method, since we do not have to assume the underlying Model function for interval Nonlinear Regression Model with crisp input and output. In particular, this method performs better and is conceptually simpler than support vector interval Regression networks (SVIRNs) which utilize two radial basis function networks to identify the upper and lower sides of data interval. Five examples are provided to show the validity and applicability of the proposed method.
Lihua Nie - One of the best experts on this subject based on the ideXlab platform.
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surface acoustic wave saw impedance sensor for kinetic assay of trypsin
Microchemical Journal, 1997Co-Authors: Qingyun Cai, Lihua Nie, Ronghui Wang, Shouzhuo YaoAbstract:Abstract The trypsin-catalyzed hydrolysis of benzoyl- l -arginine ethyl ester (BAEE) has been studied systematically at pH 7.8 and 32°C with a Nonlinear Regression Model. The Michaelis constants covering the range from pH 7.0 to 8.6 were determined. The concentrations of enzyme isolated from pig pancreas were determined using the SAW-impedance sensor and the spectrophotometry, respectively. The experimental detection limit of trypsin was 0.3 mU/ml 2 and the recovery of the sensor system ranged from 94.7 to 105% (n= 6). The effects of temperature, pH, and some metal ions on the trypsin activity were investigated.
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a Nonlinear Regression Model applied to kinetic studies of ester hydrolysis with a surface acoustic wave sensor
Talanta, 1996Co-Authors: Quingyun Cai, Ronhgui Wang, Lihua Nie, Shouzhuo YaoAbstract:Abstract A non-linear Regression Model was derived for the simultaneous determination of the rate constant in alkaline hydrolysis of esters and the initial concentration of esters based on the linear relationship between the frequency response of the surface acoustic wave sensor system and the conductivity of the solution. The Model was tested theoretically and experimentally with the methyl-, ethyl-, and n -propyl-acetate systems. The corresponding rate constants estimated at 25 °C are 0.147, 0.103 and 0.0671 respectively.
