14 Chapter 20Figure 1 ACS 2017 state estimates of the number of households (millions).Figure 2 ACS 2017 state estimates of the number of households (millions). A ...Figure 3 ACS 2017 median household income (USD) with 95% confidence interval...Figure 4 Log 10 US ACS 2017 state estimates of the number of households (per...Figure 5 ACS 2017 state estimates of the number of households (millions), wi...Figure 6 2017 ACS household median income (USD) estimates with 95% confidenc...Figure 7 Sloppy plot of 2017 ACS household median income (USD) estimates.Figure 8 Sloppy plot of 2017 ACS household median income (USD) estimates wit...Figure 9 ACS 2017 state estimates of the number of households (millions).Figure 10 ACS 2017 state estimates of the number of households (millions). T...Figure 11 2017 ACS household median income (USD) estimates with confidence i...
15 Chapter 21Figure 1 A subset of the graphical annotations used to show properties of a ...Figure 2 The process of generating a quantile dotplot from a log‐normal dist...Figure 3 Illustration of HOPs compared to error bars from the same distribut...Figure 4 Example Cone of Uncertainty produced by the National Hurricane Cent...Figure 5 (a) An example of an ensemble hurricane path display that utilizes ...
16 Chapter 22Figure 1 Classic dataflow visualization architecture.Figure 2 Client–server visualization architecture.Figure 3 (a) Piecewise linear confidence intervals and (b) bootstrapped regr...Figure 4 Dot plot and histogram.Figure 5 2D binning of 100 000 points.Figure 6 2D binning of thousands of clustered points.Figure 7 Massive data scatterplot matrix by Dan Carr [9].Figure 8 nD aggregator illustrated with 2D example.Figure 9 (a) Parallel coordinate plots of all columns and (b) aggregated col...Figure 10 Code snippets for computing statistics on aggregated data sources....Figure 11 Box plots of 100 000 Gaussians.Figure 12 Lensing a scatterplot matrix.Figure 13 Sorted and scrolling parallel coordinates [27].
17 Chapter 23Figure 1 Parallel coordinate plot of the Pima data, colored by the diabetes ...Figure 2 Heatmap of the LDA scores for measuring group separation for one an...Figure 3 PD/ICE plots for predictor smoke, from two fits to the FEV data. Ea...Figure 4 Condvis2 screenshot for a linear model and random forest fit to the...Figure 5 Condvis2 screenshot for a linear model and random forest fit to the...Figure 6 Condvis2 section plots for glucose and age from a BART (dashed line Figure 7 Condvis2 section plots for glucose and age showing classification b...Figure 8 Condvis2 section plots for mixed effects models and random forest f...Figure 9 Condvis2 section plots of two mixed effects models and a fixed effe...
18 Chapter 24Figure 1 Functional data: the hip (a) and knee (b) angles of each of the 39 ...Figure 2 The functional boxplots for the hip and knee angles of each of the ...Figure 3 The bivariate and marginal MS plots for the hip and knee angles of ...Figure 4 The two‐stage functional boxplots for the hip (a) and knee (b) angl...Figure 5 The trajectory functional boxplot (a) and the MSBD–WO plot (b) for ...
19 Chapter 26Figure 1 Minimizing
of Equation (3) via coordinate descent starting from t...
20 Chapter 29Figure 1 Simple computer surrogate model example where the response,
, is m...Figure 2 Example local designs
under MSPE and ALC criteria. Numbers plotte...Figure 3 LAGP‐calculated predictive mean on “Herbie's Tooth” data. Actually,...Figure 4 Time versus accuracy comparison on SARCOS data.
21 Chapter 31Figure 1 The organization and connections of concepts in this chapter.
22 Chapter 32Figure 1 Synchronous versus asynchronous parallel computing with shared memo...
1 Cover Page
2 Table of Contents
3 Title Page Computational Statistics in Data Science Edited by Walter W. Piegorsch University of Arizona Richard A. Levine San Diego State University Hao Helen Zhang University of Arizona Thomas C. M. Lee University of California‐Davis
4 Copyright
5 List of Contributors
6 Begin Reading
7 Index
8 Abbreviations and Acronyms
9 Wiley End User License Agreement
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