Exploration of Multivariate Data
library(gclus)
library(car)
library(MASS)
library(cluster)
library(lattice)
library(TeachingDemos)
data(wine)
# chernoff faces
faces(aggregate(wine, list(wine$Class), FUN=mean)[,-c(1,2)], ncol=3, nrow=1)
# LDA on wine data
l <- lda(Class ~ . , data=wine)
plot(l, col=wine$Class)
## Some soils data from the car package
# LDA: all horizons
l <- lda(Contour ~ pH + N + Dens + P + Ca + Ca + Mg + K + Na, data=Soils)
plot(l, col=as.numeric(Soils$Contour))
# just the top horizon
l <- lda(Contour ~ pH + N + Dens + P + Ca + Ca + Mg + K + Na, data=Soils, subset=Depth=='0-10')
plot(l, col=as.numeric(Soils$Contour[Soils$Depth == '0-10']))
Software
- General Purpose Programming with Scripting Languages
- LaTeX Tips and Tricks
- PostGIS: Spatially enabled Relational Database Sytem
- PROJ: forward and reverse geographic projections
- GDAL and OGR: geodata conversion and re-projection tools
- R: advanced statistical package
- Access Data Stored in a Postgresql Database
- Additive Time Series Decomposition in R: Soil Moisture and Temperature Data
- Aggregating SSURGO Data in R
- Cluster Analysis 1: finding groups in a randomly generated 2-dimensional dataset
- Color Functions
- Comparison of Slope and Intercept Terms for Multi-Level Model
- Comparison of Slope and Intercept Terms for Multi-Level Model II: Using Contrasts
- Creating a Custom Panel Function (R - Lattice Graphics)
- Customized Scatterplot Ideas
- Estimating Missing Data with aregImpute() {R}
- Exploration of Multivariate Data
- Interactive 3D plots with the rgl package
- Making Soil Property vs. Depth Plots
- Numerical Integration/Differentiation in R: FTIR Spectra
- Plotting XRD (X-Ray Diffraction) Data
- Using lm() and predict() to apply a standard curve to Analytical Data
- Working with Spatial Data
- Comparison of PSA Results: Pipette vs. Laser Granulometer
- GRASS GIS: raster, vector, and imagery analysis
- Generic Mapping Tools: high quality map production