First draft for second edition.

.gitignore

@@ -9,3 +9,5 @@ copy-qmds.R
 crossref.sh
 cover.png
 /.quarto/
+*.tex
+*.pdf

_quarto.yml

@@ -43,6 +43,7 @@ book:
         - inference/clt.qmd
         - inference/confidence-intervals.qmd
         - inference/hypothesis-testing.qmd
+        - inference/bootstrap.qmd
         - inference/models.qmd
         - inference/bayes.qmd
         - inference/hierarchical-models.qmd
@@ -83,6 +84,18 @@ format:
     code-link: true
     author-meta: Rafael A. Irizarry
     callout-appearance: simple
+  pdf: 
+    documentclass: krantz
+    classoption: [krantz2,10pt,twoside,onecolumn,final,openright]
+    include-in-header: preamble.tex
+    header-includes: |
+     \usepackage{amssymb}
+     \usepackage{amsmath}
+     \usepackage{graphicx}
+     \usepackage{subfigure}
+     \usepackage{makeidx}
+     \usepackage{multicol}
+    keep-tex: true
 
 knitr:
   opts_chunk:

docs/highdim/intro-highdim.html

@@ -205,23 +205,29 @@
   <a href="../inference/hypothesis-testing.html" class="sidebar-item-text sidebar-link">
  <span class="menu-text"><span class="chapter-number">9</span>&nbsp; <span class="chapter-title">Hypothesis testing</span></span></a>
   </div>
+</li>
+          <li class="sidebar-item">
+  <div class="sidebar-item-container"> 
+  <a href="../inference/bootstrap.html" class="sidebar-item-text sidebar-link">
+ <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Bootstrap</span></span></a>
+  </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../inference/models.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">10</span>&nbsp; <span class="chapter-title">Data-driven models</span></span></a>
+ <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Data-driven models</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../inference/bayes.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">11</span>&nbsp; <span class="chapter-title">Bayesian statistics</span></span></a>
+ <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Bayesian statistics</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../inference/hierarchical-models.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">12</span>&nbsp; <span class="chapter-title">Hierarchichal Models</span></span></a>
+ <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">Hierarchichal Models</span></span></a>
   </div>
 </li>
       </ul>
@@ -238,37 +244,37 @@
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../linear-models/regression.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">13</span>&nbsp; <span class="chapter-title">Regression</span></span></a>
+ <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">Regression</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../linear-models/multivariate-regression.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">14</span>&nbsp; <span class="chapter-title">Multivariate Regression</span></span></a>
+ <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Multivariate Regression</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../linear-models/measurement-error-models.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">15</span>&nbsp; <span class="chapter-title">Measurement error models</span></span></a>
+ <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Measurement error models</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../linear-models/treatment-effect-models.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">16</span>&nbsp; <span class="chapter-title">Treatment effect models</span></span></a>
+ <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Treatment effect models</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../linear-models/association-tests.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">17</span>&nbsp; <span class="chapter-title">Association tests</span></span></a>
+ <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Association tests</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../linear-models/association-not-causation.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Association is not causation</span></span></a>
+ <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Association is not causation</span></span></a>
   </div>
 </li>
       </ul>
@@ -285,31 +291,31 @@
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../highdim/matrices-in-R.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Matrices in R</span></span></a>
+ <span class="menu-text"><span class="chapter-number">20</span>&nbsp; <span class="chapter-title">Matrices in R</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../highdim/linear-algebra.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">20</span>&nbsp; <span class="chapter-title">Applied Linear Algebra</span></span></a>
+ <span class="menu-text"><span class="chapter-number">21</span>&nbsp; <span class="chapter-title">Applied Linear Algebra</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../highdim/dimension-reduction.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">21</span>&nbsp; <span class="chapter-title">Dimension reduction</span></span></a>
+ <span class="menu-text"><span class="chapter-number">22</span>&nbsp; <span class="chapter-title">Dimension reduction</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../highdim/regularization.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">22</span>&nbsp; <span class="chapter-title">Regularization</span></span></a>
+ <span class="menu-text"><span class="chapter-number">23</span>&nbsp; <span class="chapter-title">Regularization</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../highdim/matrix-factorization.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">23</span>&nbsp; <span class="chapter-title">Matrix factorization</span></span></a>
+ <span class="menu-text"><span class="chapter-number">24</span>&nbsp; <span class="chapter-title">Matrix Factorization</span></span></a>
   </div>
 </li>
       </ul>
@@ -326,49 +332,49 @@
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../ml/notation-and-terminology.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">24</span>&nbsp; <span class="chapter-title">Notation and Terminology</span></span></a>
+ <span class="menu-text"><span class="chapter-number">25</span>&nbsp; <span class="chapter-title">Notation and terminology</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../ml/evaluation-metrics.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">25</span>&nbsp; <span class="chapter-title">Evaluation metrics</span></span></a>
+ <span class="menu-text"><span class="chapter-number">26</span>&nbsp; <span class="chapter-title">Evaluation metrics</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../ml/conditionals.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">26</span>&nbsp; <span class="chapter-title">Conditional probabilities and expectations</span></span></a>
+ <span class="menu-text"><span class="chapter-number">27</span>&nbsp; <span class="chapter-title">Conditional probabilities and expectations</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../ml/smoothing.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">27</span>&nbsp; <span class="chapter-title">Smoothing</span></span></a>
+ <span class="menu-text"><span class="chapter-number">28</span>&nbsp; <span class="chapter-title">Smoothing</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../ml/cross-validation.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">28</span>&nbsp; <span class="chapter-title">Cross validation</span></span></a>
+ <span class="menu-text"><span class="chapter-number">29</span>&nbsp; <span class="chapter-title">Resampling methods</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../ml/algorithms.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">29</span>&nbsp; <span class="chapter-title">Examples of algorithms</span></span></a>
+ <span class="menu-text"><span class="chapter-number">30</span>&nbsp; <span class="chapter-title">Examples of algorithms</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../ml/ml-in-practice.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">30</span>&nbsp; <span class="chapter-title">Machine learning in practice</span></span></a>
+ <span class="menu-text"><span class="chapter-number">31</span>&nbsp; <span class="chapter-title">Machine learning in practice</span></span></a>
   </div>
 </li>
           <li class="sidebar-item">
   <div class="sidebar-item-container"> 
   <a href="../ml/clustering.html" class="sidebar-item-text sidebar-link">
- <span class="menu-text"><span class="chapter-number">31</span>&nbsp; <span class="chapter-title">Clustering</span></span></a>
+ <span class="menu-text"><span class="chapter-number">32</span>&nbsp; <span class="chapter-title">Clustering</span></span></a>
   </div>
 </li>
       </ul>
@@ -401,9 +407,9 @@ <h1 class="title">High dimensional data</h1>
 
 </header>
 
-<p>There is a variety of computational techniques and statistical concepts that are useful for analysis of datasets for which each observation is associated with a large number of numerical variables. In this chapter we provide a basic introduction to these techniques and concepts by describing matrix operations in R, dimension reduction, regularization, and matrix factorization. Handwritten digits data and movie recommendation systems serve as motivating examples.</p>
-<p>A task that serves as motivation for this part of the book is quantifying the similarity between any two observations. For example, we might want to know how much two handwritten digits look like each other. However, note that each observations is associated with <span class="math inline">\(28 \times 28 = 784\)</span> pixels so we can’t simply use subtraction as we would do if our data was one dimensional. Instead, we will define observations as <em>points</em> in a <em>high-dimensional</em> space and mathematically define a <em>distance</em>. Many machine learning techniques, discussed in the next part of the book, require this calculation.</p>
-<p>Additionally, this part of the book discusses dimension reduction. Here we search of data summaries that result in more manageable lower dimension versions of the data, but preserve most or all the <em>information</em> we need. Here too we can use distance between observations as specific challenge: we will reduce the dimensions summarize the data into lower dimensions, but in a way that preserves the distance between any two observations. We use <em>linear algebra</em> as a mathematical foundation for all the techniques presented here.</p>
+<p>There is a variety of computational techniques and statistical concepts that are useful for analysis of datasets for which each observation is associated with a large number of numerical variables. In this chapter, we provide a basic introduction to these techniques and concepts by describing matrix operations in R, dimension reduction, regularization, and matrix factorization. Handwritten digits data and movie recommendation systems serve as motivating examples.</p>
+<p>A task that serves as motivation for this part of the book is quantifying the similarity between any two observations. For example, we might want to know how much two handwritten digits look like each other. However, note that each observation is associated with <span class="math inline">\(28 \times 28 = 784\)</span> pixels so we can’t simply use subtraction as we would if our data was one dimensional. Instead, we will define observations as <em>points</em> in a <em>high-dimensional</em> space and mathematically define a <em>distance</em>. Many machine learning techniques, discussed in the next part of the book, require this calculation.</p>
+<p>Additionally, this part of the book discusses dimension reduction. Here we search for data summaries that provide more manageable lower dimension versions of the data, but preserve most or all the <em>information</em> we need. We again use distance between observations as a specific example: we will summarize the data into lower dimensions, but in a way that preserves distance between any two observations. We use <em>linear algebra</em> as a mathematical foundation for all the techniques presented here.</p>
 
 
 
@@ -644,12 +650,12 @@ <h1 class="title">High dimensional data</h1>
 <nav class="page-navigation">
   <div class="nav-page nav-page-previous">
       <a href="../linear-models/association-not-causation.html" class="pagination-link">
-        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">18</span>&nbsp; <span class="chapter-title">Association is not causation</span></span>
+        <i class="bi bi-arrow-left-short"></i> <span class="nav-page-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Association is not causation</span></span>
       </a>          
   </div>
   <div class="nav-page nav-page-next">
       <a href="../highdim/matrices-in-R.html" class="pagination-link">
-        <span class="nav-page-text"><span class="chapter-number">19</span>&nbsp; <span class="chapter-title">Matrices in R</span></span> <i class="bi bi-arrow-right-short"></i>
+        <span class="nav-page-text"><span class="chapter-number">20</span>&nbsp; <span class="chapter-title">Matrices in R</span></span> <i class="bi bi-arrow-right-short"></i>
       </a>
   </div>
 </nav>