Add to ORKGAbstract: Based on the concept of Big Data Modeling, the errors in determining peak parameters of noisy Gaussian quartets using nonlinear least squares curve fitting have been evaluated. The probability that the relative error in estimating each model parameter is not greater than a priory given limit for a given fitting error has been found. Obtained results showed that small fitting error does not guarantee that the fitting algorithm does converge to the correct peak parameters. It was found that the mean probability is a useful measure of the effectiveness of the curve fitting procedure
<p>Estimated model parameters (relative susceptibility and infectivity in children, and reproductive...
This article investigates a problem for statistical model evaluation, in particular for curve fittin...
Purpose-Curve fitting from unordered noisy point samples is needed for surface reconstruction in man...
Abstract: Based on the concept of Big Data Modeling, the errors in determining peak parameters of no...
Abstract: Errors in determining peak parameters of the huge sets of Gaussian doublets using nonlinea...
<p>This applies to both peak 0 (high, narrow peak) and peak 1 (lower, flatter peak). (with being p...
A new approach to nonlinear modeling is presented which, by incorporating the global behavior of the...
This thesis examines how to find the best fit to a series of data points when curve fitting using po...
Curve reconstruction from noisy point samples is needed for surface reconstruction in many applicati...
The purpose of this thesis is to examine different methods of curve-fitting through the process of n...
<p>(<b>A</b>) The hill-climbing results of estimating three fixed parameters (Gaussian noise σ, sigm...
This thesis is concerned with the estimation of the nonlinear parameters in statistical models consi...
In this paper, we discuss the efficiency of noise reduction for curve fitting in nonlinear growth cu...
Models based on a power law are prevalent in many areas of study. When regression analysis is perfor...
This article describes a Bayesian-based method for solving curve fitting problems. We extend the bas...
<p>Estimated model parameters (relative susceptibility and infectivity in children, and reproductive...
This article investigates a problem for statistical model evaluation, in particular for curve fittin...
Purpose-Curve fitting from unordered noisy point samples is needed for surface reconstruction in man...
Abstract: Based on the concept of Big Data Modeling, the errors in determining peak parameters of no...
Abstract: Errors in determining peak parameters of the huge sets of Gaussian doublets using nonlinea...
<p>This applies to both peak 0 (high, narrow peak) and peak 1 (lower, flatter peak). (with being p...
A new approach to nonlinear modeling is presented which, by incorporating the global behavior of the...
This thesis examines how to find the best fit to a series of data points when curve fitting using po...
Curve reconstruction from noisy point samples is needed for surface reconstruction in many applicati...
The purpose of this thesis is to examine different methods of curve-fitting through the process of n...
<p>(<b>A</b>) The hill-climbing results of estimating three fixed parameters (Gaussian noise σ, sigm...
This thesis is concerned with the estimation of the nonlinear parameters in statistical models consi...
In this paper, we discuss the efficiency of noise reduction for curve fitting in nonlinear growth cu...
Models based on a power law are prevalent in many areas of study. When regression analysis is perfor...
This article describes a Bayesian-based method for solving curve fitting problems. We extend the bas...
<p>Estimated model parameters (relative susceptibility and infectivity in children, and reproductive...
This article investigates a problem for statistical model evaluation, in particular for curve fittin...
Purpose-Curve fitting from unordered noisy point samples is needed for surface reconstruction in man...