Change Details

Following improvements are planned: 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. - DONE * use tables to improve visibility - DONE * calculate t, p- value and conf. interval of parameter - DONE * calculate p value for chi-square test - DONE * calculate p value for F test - DONE 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. see * http://stackoverflow.com/questions/22670057/linear-fitting-in-python-with-uncertainty-in-both-x-and-y-coordinates * http://stackoverflow.com/questions/12918968/gnuplot-fitting-with-error-variable-in-x-and-y E. Add button to create a label with fit results. F. implement missing fit models for statistical distributions.

Following improvements are planned: 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. - DONE * use tables to improve visibility - DONE * calculate t, p- value and conf. interval of parameter - DONE * calculate p value for chi-square test - DONE * calculate p value for F test - DONE 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. see * http://stackoverflow.com/questions/22670057/linear-fitting-in-python-with-uncertainty-in-both-x-and-y-coordinates * http://stackoverflow.com/questions/12918968/gnuplot-fitting-with-error-variable-in-x-and-y * https://www.mpp.mpg.de/~caldwell/ss05/Lecture11.pdf * http://originlab.com/doc/Origin-Help/LinearFit-XErr-Dialog * http://www.originlab.com/doc/Origin-Help/Ref-Linear-XErr * https://stats.stackexchange.com/questions/222335/line-of-best-fit-for-data-with-error-in-x-and-y * http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422013000600025 E. Add button to create a label with fit results. F. implement missing fit models for statistical distributions.

Following improvements are planned: 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. - DONE * use tables to improve visibility - DONE * calculate t, p- value and conf. interval of parameter - DONE * calculate p value for chi-square test - DONE * calculate p value for F test - DONE 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. see * http://stackoverflow.com/questions/22670057/linear-fitting-in-python-with-uncertainty-in-both-x-and-y-coordinates * http://stackoverflow.com/questions/12918968/gnuplot-fitting-with-error-variable-in-x-and-y * https://www.mpp.mpg.de/~caldwell/ss05/Lecture11.pdf * http://originlab.com/doc/Origin-Help/LinearFit-XErr-Dialog * http://www.originlab.com/doc/Origin-Help/Ref-Linear-XErr * https://stats.stackexchange.com/questions/222335/line-of-best-fit-for-data-with-error-in-x-and-y * http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-40422013000600025 E. Add button to create a label with fit results. F. implement missing fit models for statistical distributions.