Search
You can find the results of your search below.
Fulltext results:
- bootstrap
- basis of the experimental data and repeating the fit for these simulated data sets. The spread of all the best fit paramter sets generated by these fits serves as a measure for the parameter errors. Specifically, the... at least 1000 data sets have to be simulated and fitted, the bootstrap method seems to be rather time ... nalysis]] and thus can be applied even to [[MLE]] fitting. ===== Implementation ===== The implementa
- marquardt-levenberg
- to be replaced by [[MLE]] fitting. When running a [[MLE]] fit the SymPhoTime software abandons the ML-fitting and switches to a gradient search.
- support_plane_analysis
- he support plane analysis is used for analysing [[fitting]] parameter error intervals. It works by calc... r space. For illustration let's start at the best fit parameter set, which can be regarded as a single ... s done by keeping the removed parameter fixed and fitting all the other parameters. By this we deviate ... ===== Advantages and disadvantages ===== Since [[fitting]] is used to derive a functional dependence o
- chi_square_management
- the optimization parameter for [[least squares]] fitting (for a definition see there). For a perfect fit it should be near 1. As a measure of the goodness-of-fit it is insufficient. Other methods have to be used
- least_squares
- gm for matching data ('{{wiki>Regression_analysis|fitting}}') with a parametrised model equation. A fam... s. The least squares measure for the goodness-of-fit is $$\chi ^2_{red}=\frac{1}{N-n_p}\sum_{i=1}^{N}
- asymptotic_standard_errors
- otic standard errors (ASE) are used for analyzing fitting parameter error intervals. For illustration let's start at the best fit parameter set, which can be regarded as a single
- residuals
- squares]] (or any other [[wp>Regression_analysis|fitting]] method, e.g. [[MLE]]) the residuals are the... of importance within any framework concerned with fitting, as the [[software:SymPhoTime]] software or [
- poisson_distribution
- nu}^{}_{}$. In the Gaussian limit [[least squares]] [[wp>Regression_analysis|fitting]] may be applied, otherwise [[MLE]] [[wp>Regression_analysis|fitting]] is preferable.
- monte_carlo
- nding initial values for [[wp>Regression_analysis|fitting]] parameters before optimisation by a [[Marqu
- fast_lifetime
- e single path calculation, compared to a complete fitting operation against a more complex, non-linear