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Aspen Unscrambler
巨變量分析及實驗設計軟體
Multivariate Analysis and Experimental Design software
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Features

Descriptive Statistics

Mean/ Std Dev/ Quartiles/ Cross Correlations/ Scatter Effects

Statistical Tests

Normality Test/ t-Tests/ F-Tests/ Mardia’s Multivariate Test

Cluster Analysis

K-means / K-medians Ward’s method

Hierarchical Cluster Analysis (HCA) with dendrograms

Principal Component Analysis (PCA)

Choice of using NIPALS or SVD algorithms

Rotation methods including Varimax, Equimax, Quartimax and Parsimax

Multivariate Curve Resolution (MCR)

Resolve time evolving data such as chemical reaction or chromatographic data into pure constituent profiles and pure spectra

Regression Methods

Multiple Linear Regression (MLR) / Principal Component Regression (PCR) and Partial Least Squares Regression (PLSR)

Choice of algorithms, NIPALS and SVD for PCR and NIPALS, Kernel Methods and Orthogonal Scores for PLSR
Improved Test Set Validation options

Q-Residuals in influence plots
L-PLS, incorporating three data tables for greater insights into data structure

Advanced Classification Methods

Projection using PCA and PLS models

Soft Independent Modelling of Class Analogy (SIMCA) now also incorporating PLS models

Linear Discriminant Analysis (LDA)

Support Vector Machines (SVM) Classification with numerous kernel types

Spectral Functions

Smoothing

Derivatives: Moving Average/ Norris Gap/ Savitzky-Golay

Baseline Correction

Normalization

Spectroscopic: Reflectance/ Transmission/ Kubelka-Munck

Scatter Correction and Advanced Functions

Multiplicative and Extended Multiplicative Scatter Correction (MSC/ EMSC)

Standard Normal Variate (SNV)

Deresolve

Detrending

General Transforms

Improved Centre and Scale options

Spectroscopic: Reflectance/ Transmission/ Kubelka-Munck

Interaction & Squares and Individual Variable Weighting

Compute General

Fill Missing Values

Correlation Optimization Warping (COW)

Improved Design Wizard

Interactive design setup with full descriptions and Beginner/ Expert modes

Complete range of full and fractional factorial designs

Enhanced optimization designs including Central Composite (CCD) and Box-Behnken (BB) designs

Enhanced mixture designs including Axial, Simplex Lattice and Simplex Centroid designs

Choice of Analysis Algorithms

Classical MLR and ANOVA-PLS for non-orthogonal designs

PLSR or Scheffe Polynomials for mixture designs

Comprehensive Analysis Overview

ANOVA tables and other tabular results

Cube Plots

Response Surfaces

Analysis of Effects

Interactive Tables
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