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Principal Components Analysis (PCA)
- Data Selection Options
- Transpose Rows/Columns
- Assign score plot labels
- Group/Responses
- Preprocessing options
- Preprocessing columns
- Centre Data?
- Log Transform Data?
- Add Offset to Data?
- Scale by SD?
- Pareto Scaling?
- No scaling?
- Preprocessing rows (observations)
- Smooth?
- Moving Average
- Quadratic/Cubic
- Quartic/Quintic
- Window
- Baseline Correct?
- Derivative Order
- Polynomial Order
- Quadratic/Cubic
- Window
- Standardise/Normalise
- Analysis Options
- PCA or PCA Group?
- Number of Components
- Number to display
- Eigenvalues >
- Perform Cross Validation?
- Output results to a datasheet?
- Missing Data Estimating Options
- Maximum number of iterations
- Tolerance level for convergence
- Continue of fail to converge?
- Suppress convergence messages?
- Results Table
- Eigenvalues
- R2
- R2(Cum)
- Charts
- Variance explained by each PC
- PCA scores plot, any X vs Y
- PCA loadings plot, any X vs Y
- Distance to Model, for each sample
- Modelling Power, for each variable
Basic Stats
- Sample Count
- Mean
- Median
- Minimum / Maximum
- Range (Min-Max)
- Lower / Upper Quartile
- Variance
- Standard Deviation
- Standard Error of Mean
- Coefficient of Variation
- Lower/Upper Confidence Interval
- Skewness
- Kurtosis
