ZunZunNG - Reciprocal Simple Equation 24 Fitting Interface

Introduction

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

Text data editor

Cut-and-paste text or edit data here

Comma conversion

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)

Weighted fitting

Standard Unweighted Fitting: no weights required

Weighted Fitting: each data point requires a weight

Text data

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. X Y Z 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.

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)

Graph scaling and lin/log control

Here you can choose the scaling of the data plots and the 3D scatterplots. Log plots require data values greater than zero.

X Axis Scale

Autoscale +/- 1%

Autoscale +/- 2.5%

Autoscale +/- 5%

Autoscale +/- 10%

Autoscale +/- 25%

Autoscale +/- 50%

Autoscale +/- 100%

Autoscale +/- 150%

Autoscale +/- 200%

Manual Scale

Max X: Min X:

Linear Scaling

Logarithmic Scaling

Y Axis Scale

Autoscale +/- 1%

Autoscale +/- 2.5%

Autoscale +/- 5%

Autoscale +/- 10%

Autoscale +/- 25%

Autoscale +/- 50%

Autoscale +/- 100%

Autoscale +/- 150%

Autoscale +/- 200%

Manual Scale

Max Y: Min Y:

Linear Scaling

Logarithmic Scaling

Z Axis Scale

Autoscale +/- 1%

Autoscale +/- 2.5%

Autoscale +/- 5%

Autoscale +/- 10%

Autoscale +/- 25%

Autoscale +/- 50%

Autoscale +/- 100%

Autoscale +/- 150%

Autoscale +/- 200%

Manual Scale

Max Z: Min Z:

Linear Scaling

Logarithmic Scaling

Graph and Animation size

Here you can choose the size of the graphs. Smaller size files load quickly, with less resolution while large files show more resolution but load more slowly.

Graph Size

Graph size

320 × 240 (fastest)

500 × 400

640 × 480

700 × 500

800 × 600

900 × 700

1024 × 768

1280 × 1024

1600 × 1200 (slowest)

wide ratio 2400 × 400

Animation Size

Animation size

320 × 240 (smallest)

500 × 400

640 × 480

700 × 500

800 × 600

900 × 700 (largest)

No Animations

Scientific Notation

Here you can control scientific notation on the data plots and the contour plots.

X Scientific Notation

Off

Auto

Y Scientific Notation

Off

Auto

Z Scientific Notation

Off

Auto

Hold Coefficients Constant

Here you can enter values to hold coefficients constant during fitting.
Leave the entry field blank to let the coefficient fit normally.

Note that coefficient bounds are overridden by holding a coefficient constant.

z = a*pow(x,b+c*ln(y))
z = 1.0 / z

Coefficient	Value
a
b
c

Estimated Initial Coefficients

Here you can enter values for initial parameter estimates.

Few users will need this section, as the site estimates initial parameters using the Differential Evolution genetic algorithm for both non-linear equations and non-Gaussian fitting targets.

z = a*pow(x,b+c*ln(y))
z = 1.0 / z

Coefficient	Value
a
b
c

Coefficient Bounds

Here you can enter coefficient upper and lower bounds. Leave the entry fields blank to let the coefficients fit without bounds.

Note that holding a coefficient constant overrides these bounds.

z = a*pow(x,b+c*ln(y))
z = 1.0 / z

Coefficient	Upper Bound	Lower Bound
a
b
c

3D Viewing Angles

Here you can select and rotate the 3D scatter and surface plots.

Rotation view angle in degrees: Vertical view angle in degrees:

3D Data Point Size Options

Here you can select the data point size for 3D surface plots and 3D scatter plots.

3D Point Size

3D data point size

Tiny

Small

Medium

Large

Extra Large

Auto