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.
More Power and Sample Size