Copy/paste operation can offer a flexible way to copy fitting analysis operation to all curve in another graph. Following analysis supports this feature
- Linear Fit
- Nonlinear Curve/Implicit Curve/Surface Fit
- Nonlinear Matrix Fit
- Polynomial Fit
- Other special nonlinear curve fitting operations(Exepential Fit/Single Peak Fit/Sigmoidal Fit)
Akima Spline Interpolation
Akima Spline is a robust interpolation method for data sets with outliers
Lowess and Loess method for Data Smoothing
Partial Least Squares Regression
Partial least squares (PLS) is a method for constructing predictive models when the factors are many and highly collinear. It is useful for variable selection and dimension reduction
There are two primary reason for using PLS
- Prediction
PLS is most commonly used for constructing predictive model when the the information contained in a large number of original variables and they are highly collinear.
- Interpretation
PLS can be used to discover important features of a large data set. It often reveals relationships that were previously unsuspected, thereby allowing interpretations of the data that may not ordinarily result from examination of the data.
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- BIC Test for Model Comparison
- Fit Comparison Improvements
- LR/PR: Show Parameter Values in Equation
- Custom X Values for Fitted Curve
- Enable ODR for Explicit Function Fit (Pro)
- Add Fitted Surface to 3D Source Graph
- Fit and Rank All Functions in a Category
- Partial Least Squares Regression (Pro)
- Outlier Tests added to Menu
- More Power & Sample Size Tests (Pro)
- Proportion Testing in Hypothesis Testing (Pro)
- Arrange graph of same type in one graph in applicable statistics
- More statistics quantities For Pair Sample t-Test
- Weibull Fit: Show Probability Plot with Confidence Limits
Signal Processing