Análise Multivariada

Plano de Curso 2019
Aulas Teóricas
- MA P1: Introduction and pattern recognition
- MA P2: Univariate statistics
- MA P3: Multivariate data
- MA P4: PCA
- T05: calibration part1 & part2
- T06: classification
  - example_plsda.r.7z
- T07: cluster analysis
Aulas Práticas
- P01: Learning R
  - swirl (Learn R, in R and The Swirl Course Network)
  - DataCamp’s free R Tutorial
  - The 5 most effective ways to learn R
  - RStudio's Online Learning
- P02: Exploratory data analysis
  - R-bloggers
    - Exploratory data analysis in R
    - Exploratory data analysis using R (part-I)
  - univariate and bivariate data analysis
  - EDA (R for DataScience)
  - exploratory data analysis with R
  - Simple fast exploratory data analysis in R with dataexplorer package
  - estatística univariada (partes 1 e 2)
- P03: Preprocessing
  - Basic preprocessing
  - An Introduction to ChemoSpec (até item 6 que acaba na pág 9)
  - Preprocessing - Getting started with mdatools for R
  - An introduction to the prospectr package
- P04: pca
- P05: eda
  - pca and clustering
  - Kohonen mapping
- P06: Regression models
- P07: PLS and ridge regressions
- P08: LDA and PCA
  - computing and visualizing LDA in R (by Thiago G. Martins)
  - using R for multivariate analysis
- P09: classification part1
  - discriminant function analysis
  - knn
- P10: classification part2
- P11: cluster analysis part1: k-means
  - k-means clustering
  - r scripts (Penn State Univ)
  - how to produce a pretty plot of the results of k-means cluster analysis?
- P12: cluster analysis part2
  - quick-R: cluster analysis
  - item 4 (case studies) in ward´s hierarchical clustering method
  - cluster tendency
    - assessing cluster tendency in R
    - assessing cluster tendency: a vital issue

Dados
- NO3.txt: teores de nitrato em 50 amostras de água
Internet R documentation
- A. Coghran's little books of R for...
- Box-plot
  - box-plot basics
  - box-plot with R
- Exploratory data analysis

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