References
R for Research in Action
Preface
Introduction
1
R Objects
2
Data Types
3
Packages
4
Code Style
Part 1: Manipulating Data
5
Reading Data
6
Writing Data
7
Tidy Data
8
Transforming Data
9
Subsetting R Objects
10
Plyr & Dplyr
11
Date Manipulation
12
Text Manipulation
13
R and Data Bases
Part 2: Statistics in R
14
Descriptive Statistics
15
Exploratory Analysis Pipeline
16
Inferential Statistics
17
Regression Analysis
Part 3: Programming in R
18
Programming Habits
19
Logic
20
Functions
21
Iteration
22
Debugging
23
Profiling R Code
Part 4: Graphics
24
Graphs
25
Creating a ggplot
26
Types of Graphs
Part 5: Modeling
27
Modeling Workflow
28
Spending Your Data
29
Fitting Models
30
Random Numbers
Part 6: Time Series
31
TS Analysis
32
TS Objects
33
TS Components
34
Decomposition of TS
35
Seasonality Analysis
36
Correlation Analysis
37
Forecasting Basics
38
Forecasting with Smoothing Methods (MA Models)
39
Forecasting with Exponential Smoothing
40
Forecasting with Linear Regression
41
Forecasting with ARIMA Models
42
Forecasting with Machine Learning Models
Part 7: Data Products
43
Building Data Products
44
Reproducible Reporting
References
References
44
Reproducible Reporting