Change Details

Following improvements should be checked: A. Find fit parameter in user supplied fit function automatically - DONE Currently the fit parameter has to be given by the user which is more work than necessary. We should check if we can get this information from the parser. B. Improve output of results. * use tables to improve visibility - DONE * calculate t, p- value and conf. interval of parameter - DONE * calculate p value for chi-square test - CHECK * calculate p value for F test - TODO see * https://reference.wolfram.com/language/howto/FitModelsWithMeasurementErrors.html * https://de.wikipedia.org/wiki/Einstichproben-t-Test * http://reliawiki.org/index.php/Multiple_Linear_Regression_Analysis#Estimating_Regression_Models_Using_Least_Squares * https://onlinecourses.science.psu.edu/stat501/node/297 * http://reliawiki.org/index.php/Simple_Linear_Regression_Analysis C. support different weighting types. see http://www.originlab.de/doc/Origin-Help/FIt-with-Err-Weight, http://reference.wolfram.com/language/ref/Weights.html, http://www.graphpad.com/guides/prism/6/curve-fitting/index.htm?reg_weighted_nonlinear_regression.htm D. support x-errors for fitting. E. Add button to create a label with fit results. F. implement missing fit models for statistical distributions.

Following improvements should be checked: A. Find fit parameter in user supplied fit function automatically - DONE Currently the fit parameter has to be given by the user which is more work than necessary. We should check if we can get this information from the parser. B. Improve output of results. * use tables to improve visibility - DONE * calculate t, p- value and conf. interval of parameter - DONE * calculate p value for chi-square test - CHECK * calculate p value for F test - TODO see * https://reference.wolfram.com/language/howto/FitModelsWithMeasurementErrors.html * https://de.wikipedia.org/wiki/Einstichproben-t-Test * http://reliawiki.org/index.php/Multiple_Linear_Regression_Analysis#Estimating_Regression_Models_Using_Least_Squares * https://onlinecourses.science.psu.edu/stat501/node/297 * http://reliawiki.org/index.php/Simple_Linear_Regression_Analysis * https://onlinecourses.science.psu.edu/stat501/node/295 C. support different weighting types. see * http://www.originlab.de/doc/Origin-Help/FIt-with-Err-Weight * http://reference.wolfram.com/language/ref/Weights.html * http://www.graphpad.com/guides/prism/6/curve-fitting/index.htm?reg_weighted_nonlinear_regression.htm D. support x-errors for fitting. E. Add button to create a label with fit results. F. implement missing fit models for statistical distributions.

Following improvements should be checked: A. Find fit parameter in user supplied fit function automatically - DONE Currently the fit parameter has to be given by the user which is more work than necessary. We should check if we can get this information from the parser. B. Improve output of results. * use tables to improve visibility - DONE * calculate t, p- value and conf. interval of parameter - DONE * calculate p value for chi-square test - CHECK * calculate p value for F test - TODO see * https://reference.wolfram.com/language/howto/FitModelsWithMeasurementErrors.html * https://de.wikipedia.org/wiki/Einstichproben-t-Test * http://reliawiki.org/index.php/Multiple_Linear_Regression_Analysis#Estimating_Regression_Models_Using_Least_Squares * https://onlinecourses.science.psu.edu/stat501/node/297 * http://reliawiki.org/index.php/Simple_Linear_Regression_Analysis * https://onlinecourses.science.psu.edu/stat501/node/295 C. support different weighting types. see * http://www.originlab.de/doc/Origin-Help/FIt-with-Err-Weight * http://reference.wolfram.com/language/ref/Weights.html see http://www.originlab.de/doc/Origin-Help/FIt-with-Err-Weight, http://reference.wolfram.com/language/ref/Weights.html,* http://www.graphpad.com/guides/prism/6/curve-fitting/index.htm?reg_weighted_nonlinear_regression.htm D. support x-errors for fitting. E. Add button to create a label with fit results. F. implement missing fit models for statistical distributions.