image from: R Project

R from Dummies

Maybe you think the title is wrong. It should be R for Dummies. No, itsn't, because I am just about a month a go running R as daily habit, although I have installed the R package and R Studio since two years a go. At first I only used it as tools for hydrological modeling, but now I use it for many kind of activity, including blog posting.
As for this page, I wasn't intentionally build it as a tutorial page, but more like to show what I've learned and done with R. So it will be un-structured and scattered, as I invreasingly use it to solve my problems or several tutorial that I follow. But I try to divide it in to parts from the simplest code (for me) towards the hardest code. But I can guarantee that it won't be so complicated though. Remember it's R from Dummies.
So here we go...

The one with the introduction

1. 0.1 How to cite R (R for beginners)
2. 1.1 R the 18th letter: R for beginners
3. 1.2 Why R (R for beginners)
4. 1.3 An R historical glimpse
5. 1.4 R environment (R for beginners)
6. 1.5 R installation (R for beginners)
7. Part 2: StartingR (R for beginners)
8. 2.1 Some R cool stuffs for motivation (R for beginners)
9. 3rd Workshop Introduction to R
10. Tabel of contents: 3rd Workshop Introduction to R

The one with chart plotting

1. [exercise] My first plot
2. [exercise] Plotting groundwater and river water TDS
3. QQ plot in R
4. Linear regression: in Excel and R
5. Plotting selangkah demi selangkah dengan R

The one with basic statistic analysis

1. dplyr package exercise: in Indonesia language

The one with multivariate analysis

1. Heatmap and corrgram to evaluate student's scores (updated)
2. Twitter data mining: first try out
3. Matrix aggregation (finalized post)

The one with hydrological modeling

1. Lumped vs distributed model
2. How to install Hydromad Package on Mac OSX Lion
3. Following the hydromad tutorial by Felix Andrews
4. Hydromad application to Cikapundung Catchment: an exercise

The one with spatial analysis

1. Preliminary "mgcv" result
2. Looking at the predictors to water quality: using GAM
3. Updated #R Code: GAM exercise using mgcv package
4. #R: GAM exercise using mgcv package (the workflow)
5. hydrogeological analysis using open source tools: case Cikapundung River