Home Page Icon
Home Page
Table of Contents for
Getting ready
Close
Getting ready
by Francisco Juretig
R Statistics Cookbook
Title Page
Copyright and Credits
R Statistics Cookbook
About Packt
Why subscribe?
Packt.com
Contributors
About the author
About the reviewer
Packt is searching for authors like you
Preface
Who this book is for
What this book covers
To get the most out of this book
Download the example code files
Download the color images
Conventions used
Sections
Getting ready
How to do it…
How it works…
There's more…
See also
Get in touch
Reviews
Getting Started with R and Statistics
Introduction
Technical requirements
Maximum likelihood estimation
Getting ready
How to do it...
How it works...
There's more...
See also
Calculating densities, quantiles, and CDFs
Getting ready
How to do it...
How it works...
There's more...
Creating barplots using ggplot
Getting ready
How to do it...
How it works...
There's more...
See also
Generating random numbers from multiple distributions
Getting ready
How to do it...
How it works...
There's more...
Complex data processing with dplyr
Getting ready
How to do it...
How it works...
There's more...
See also
3D visualization with the plot3d package
Getting ready
How to do it...
How it works...
Formatting tabular data with the formattable package
Getting ready
How to do it...
How it works...
There's more...
Simple random sampling
Getting ready
How to do it...
How it works...
Creating diagrams via the DiagrammeR package
Getting ready
How to do it...
How it works...
See also
C++ in R via the Rcpp package
Getting ready
How to do it...
How it works...
See also
Interactive plots with the ggplot GUI package
Getting ready
How to do it...
How it works...
There's more...
Animations with the gganimate package
Getting ready
How to do it...
How it works...
See also
Using R6 classes
Getting ready
How to do it...
How it works...
There's more...
Modeling sequences with the TraMineR package
Getting ready
How to do it...
How it works...
There's more...
Clustering sequences with the TraMineR package
Getting ready
How to do it...
How it works...
There's more...
Displaying geographical data with the leaflet package
Getting ready
How to do it...
How it works...
Univariate and Multivariate Tests for Equality of Means
Introduction
The univariate t-test
Getting ready
How to do it...
How it works...
There's more...
The Fisher-Behrens problem
How to do it...
How it works...
There's more...
Paired t-test
How to do it...
How it works...
There's more...
Calculating ANOVA sum of squares and F tests
How to do it...
Two-way ANOVA
How to do it...
How it works...
There's more...
Type I, Type II, and Type III sum of squares
Type I
Type II
Type III
Getting ready
How to do it...
How it works...
Random effects
Getting ready
How to do it...
How it works...
There's more...
Repeated measures
Getting ready
How to do it...
How it works...
There's more...
Multivariate t-test
Getting ready...
How to do it...
How it works...
There's more...
MANOVA
Getting ready
How to do it...
How it works...
There's more...
Linear Regression
Introduction
Computing ordinary least squares estimates 
How to do it...
How it works...
Reporting results with the sjPlot package 
Getting ready 
How to do it...
How it works...
There's more...
Finding correlation between the features 
Getting ready... 
How to do it... 
Testing hypothesis 
Getting ready 
How to do it... 
How it works... 
Testing homoscedasticity 
Getting ready 
How to do it... 
How it works...
Implementing sandwich estimators 
Getting ready 
How to do it... 
How it works...
Variable selection 
Getting ready 
How to do it... 
How it works... 
Ridge regression 
Getting ready 
How to do it... 
How it works... 
Working with LASSO 
Getting ready 
How to do it...
How it works...
There's more...
Leverage, residuals, and influence 
Getting ready 
How to do it...
How it works... 
Bayesian Regression
Introduction
Getting the posterior density in STAN 
Getting ready
How to do it...
How it works...
Formulating a linear regression model
Getting ready
How to do it...
How it works...
There's more...
Assigning the priors
Defining the support
How to decide the parameters for a prior
Getting ready
How to do it...
How it works...
Doing MCMC the manual way
Getting ready
How to do it...
How it works...
Evaluating convergence with CODA
One or multiple chains?
Getting ready
How to do it...
How it works...
There's more...
Bayesian variable selection
Getting ready
How to do it...
How it works...
There's more...
See also
Using a model for prediction
Getting ready
How to do it...
How it works...
GLMs in JAGS
Getting ready
How to do it...
How it works...
Nonparametric Methods
Introduction
The Mann-Whitney test
How to do it...
How it works...
There's more...
Estimating nonparametric ANOVA
Getting ready
How to do it...
How it works...
The Spearman's rank correlation test
How to do it...
How it works...
There's more...
LOESS regression
Getting ready
How to do it...
How it works...
There's more...
Finding the best transformations via the acepack package
Getting ready
How to do it...
How it works...
There is more...
Nonparametric multivariate tests using the npmv package
Getting ready
How to do it...
How it works...
Semiparametric regression with the SemiPar package
Getting ready
How to do it...
How it works...
There's more...
Robust Methods
Introduction
Robust linear regression
Getting ready
How to do it...
How it works...
Estimating robust covariance matrices
Getting ready
How to do it...
How it works...
Robust logistic regression
Getting ready
How to do it...
How it works...
Robust ANOVA using the robust package
Getting ready
How to do it...
How it works...
Robust principal components
Getting ready
How to do it...
How it works...
Robust Gaussian mixture models with the qclust package
Getting ready
How to do it...
How it works...
Robust clustering
Getting ready
How to do it...
How it works...
Time Series Analysis
Introduction
The general ARIMA model 
Getting ready
How to do it...
How it works...
Seasonality and SARIMAX models 
Getting ready
How to do it...
There's more...
Choosing the best model with the forecast package 
Getting ready
How to do it...  
How it works... 
Vector autoregressions (VARs)  
Getting ready
How to do it...  
How it works... 
Facebook's automatic Prophet forecasting  
Getting ready
How to do it...  
How it works...
There's more...
Modeling count temporal data 
Getting ready
How to do it... 
There's more...
Imputing missing values in time series  
Getting ready
How to do it...
How it works... 
There's more... 
Anomaly detection 
Getting ready
How to do it... 
How it works... 
There's more... 
Spectral decomposition of time series 
Getting ready
How to do it... 
How it works... 
Mixed Effects Models
Introduction
The standard model and ANOVA 
Getting ready
How to do it...
How it works... 
Some useful plots for mixed effects models 
Getting ready
How to do it... 
There's more... 
Nonlinear mixed effects models 
Getting ready
How to do it... 
How it works... 
There's more... 
Crossed and nested designs 
Crossed design 
Nested design 
Getting ready 
How to do it... 
How it works.. 
Robust mixed effects models with robustlmm 
Getting ready
How to do it... 
How it works... 
Choosing the best linear mixed model
Getting ready 
How to do it... 
How it works... 
Mixed generalized linear models 
Getting ready
How to do it... 
How it works... 
There's more...
Predictive Models Using the Caret Package
Introduction
Data splitting and general model fitting
Getting ready
How to do it...
How it works...
There's more...
See also
Preprocessing
Getting ready
How to do it...
How it works...
Variable importance and feature selection
Getting ready
How to do it...
How it works...
Model tuning
Getting ready
How to do it...
How it works...
Classification in caret and ROC curves
Getting ready
How to do it...
How it works...
Gradient boosting and class imbalance
Getting ready
How to do it...
How it works...
Lasso, ridge, and elasticnet in caret
Getting ready
How to do it...
How it works...
Logic regression
Getting ready
How to do it...
How it works...
Bayesian Networks and Hidden Markov Models
Introduction
A discrete Bayesian network via bnlearn
Getting ready
How to do it...
How it works...
There's more...
See also
Conditional independence tests
Getting ready
How to do it...
How it works...
There's more...
Continuous and hybrid Bayesian networks via bnlearn
Getting ready
How to do it...
How it works...
See also
Interactive visualization of BNs with the bnviewer package
Getting ready
How to do it...
How it works...
An introductory hidden Markov model
Getting ready
How to do it...
How it works...
There's more...
Regime switching in financial data via HMM
Getting ready
How to do it...
How it works...
There's more...
Other Books You May Enjoy
Leave a review - let other readers know what you think
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Prev
Previous Chapter
Model tuning
Next
Next Chapter
How to do it...
Getting ready
The
caret
package needs to be installed using
install.packages("caret")
.
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset