Akima Spline Interpolation
Akima Spline is a robust interpolation method for data sets with outliers
LOWESS and LOESS Smoothing
Loess and Lowess are methods to describes the deterministic part of the variation in the data without requirement of a specific function. They are especially useful for detecting the trend of the data.
...
- 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
...
...
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
In Origin 9.1, it is supported more test for Power and Sample Size
- One Proportion Test
- Two Proportion Test
- One Variance Test
...
Features not Finished in Beta 2
Features listed below are not finished yet in Origin 9.1 beta2
...
- 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