Companion to the Book "Computational Statistics with R"

Provides data sets and functions used in the book "Computational Statistics with R" (< https://cswr.nrhstat.org>).

CSwR

The CSwR package is a companion to the book Computational Statistics with R available at cswr.nrhstat.org. It provides data and utility functions used throughout the book for teaching computational statistics concepts.

Installation

You can install the latest version from CRAN with:

install.packages("CSwR")

Or install the development version from GitHub with:

# install.packages("pak")
pak::pak("jolars/CSwR-Package")

Features

The package includes:

Datasets: Five datasets used in examples throughout the book:
- greenland - Monthly temperature data from southwest Greenland (1873-2013)
- nuuk - Annual temperature summaries for Nuuk (1867-2013)
- vegetables - Weekly frozen vegetable sales data
- angle - Torsion angles from protein structure (1HMP)
- news - Social media news sharing features from Mashable articles
Tracer objects (tracer()) - Collect, print, and visualize trace information during function evaluation for debugging and performance analysis
Terminator objects (terminator()) - Define termination conditions for iterative algorithms with callback support
Random number streams (rng_stream()) - Efficient cached random number generation
Force evaluation (force_all()) - Utility to force evaluation of all function arguments and avoid lazy evaluation pitfalls
Plotter expressions (plotter()) - Create expressions for iterative plot updates during long-running computations

Usage

library(CSwR)

# Load and explore datasets
data(greenland)
head(greenland)

  Year Month Temp_nuuk Temp_Qaqortoq Temp_diff
1 1873     1     -12.1          -9.9      -2.2
2 1874     1     -13.1         -11.6      -1.5
3 1875     1      -6.6          -6.3      -0.3
4 1876     1     -11.1          -8.3      -2.8
5 1877     1     -14.5          -8.8      -5.7
6 1878     1      -7.7          -6.8      -0.9

# Create a tracer for monitoring algorithm progress
tr <- tracer(c("x", "residual"), time = TRUE)
# Use tr$tracer as a callback in your iterative function

# Set up a terminator with a convergence condition
term <- terminator(cond = quote(residual < 1e-6), Delta = 10)
# Returns TRUE when condition is met