Introduction

Please select an option from the pull-down menu above.

Advice: Most users should turn off the Polyfunctional family
of equations and set the Smoothness Control to a small value
to start, then increase the Smoothness Control value as needed.

Text data editor

Cut-and-paste text or edit data here

Convert commas to spaces (1,2,0,3 yields 1 2 0 3) Use comma as decimal separator (1,203 = 1.203) Remove commas from text (1,2,0,3 yields 1203)

Standard Unweighted Fitting: no weights required Weighted Fitting: each data point requires a weight

This data is provided as an example, cut and paste as needed to model your data. All lines of text that do not begin with a number are ignored. Weighted fitting requires an additional number to be used as a weight when fitting. The site does not calculate any weights, which are used as: error = weight * (predicted - actual) You must provide any weights you wish to use. 3.017 2.175 0.320 2.822 2.624 0.629 2.632 2.839 0.950 2.287 3.030 1.574 2.207 3.057 1.725 2.048 3.098 2.035 1.963 3.115 2.204 1.784 3.144 2.570 1.712 3.153 2.721 2.972 2.106 0.313 2.719 2.542 0.643 2.495 2.721 0.956 2.070 2.878 1.597 1.969 2.899 1.758 1.768 2.929 2.088 1.677 2.939 2.240 1.479 2.957 2.583 1.387 2.963 2.744 2.843 1.984 0.315 2.485 2.320 0.639 2.163 2.444 0.954 1.687 2.525 1.459 1.408 2.547 1.775 1.279 2.554 1.927 1.016 2.564 2.243 0.742 2.568 2.581 0.607 2.571 2.753

Fitting Target

Here you can select the desired fitting target.

Lowest sum of squared absolute error Lowest sum of squared orthogonal distance Lowest sum of squared relative error Lowest sum of absolute value of absolute error Lowest sum of squared log[predicted/actual] Lowest sum of absolute value of relative error Lowest peak absolute value of absolute error Lowest peak absolute value of relative error Lowest Akaike Information Criterion Lowest Bayesian Information Criterion

Data labels for graphs

Here you can enter the X, Y and Z data labels to be printed on the report graphs.

Label for first independent data (X)

Label for second independent data (Y)

Label for dependent data (Z)