Data Science in Theory and Practice. Maria Cristina Mariani

nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.

       Library of Congress Cataloging‐in‐Publication Data applied for

      ISBN: 9781119674689

      Cover Design: Wiley

      Cover Image: © nobeastsofierce/Shutterstock

List of Figures

      Figure 4.1 Time series data of phase arrival times of an earthquake.

      Figure 4.2 Time series data of financial returns corresponding to Bank of America (BAC) stock index.

      Figure 4.3 Seasonal trend component.

      Figure 4.4 Linear trend component. The horizontal axis is time

, and the vertical axis is the time series

. (a) Linear increasing trend. (b) Linear decreasing trend.

      Figure 4.5 Nonlinear trend component. The horizontal axis is time

and the vertical axis is the time series

. (a) Nonlinear increasing trend. (b) Nonlinear decreasing trend.

      Figure 4.6 Cyclical component (imposed on the underlying trend). The horizontal axis is time

and the vertical axis is the time series

.

      Figure 7.1 The big O notation.

      Figure 7.2 The

notation.

      Figure 7.3 The

notation.

      Figure 7.4 Symbols used in flowchart.

      Figure 7.5 Flowchart to add two numbers entered by user.

      Figure 7.6 Flowchart to find all roots of a quadratic equation

.

      Figure 7.7 Flowchart.

      Figure 8.1 The box plot.

      Figure 8.2 Box plot example.

      Figure 9.1 Scatter plot of temperature versus ice cream sales.

      Figure 9.2 Heatmap of handwritten digit data.

      Figure 9.3 Map of earthquake magnitudes recorded in Chile.

      Figure 9.4 Spatial distribution of earthquake magnitudes (Mariani et al. 2016).

      Figure 9.5 Number of text messages sent.

      Figure 9.6 Normal Q–Q plot.

      Figure 9.7 Risk of loan default. Source: Tableau Viz Gallery.

      Figure 9.8 Top five publishing markets. Source: Modified from International Publishers Association – Annual Report.

      Figure 9.9 High yield defaulted issuer and volume trends. Source: Based on Fitch High Yield Default Index, Bloomberg.

      Figure 9.10 Statistics page for popular movies and cinema locations. Source: Google Charts.

      Figure 10.1 One‐step binomial tree for the return process.

      Figure 11.1 Height versus weight.

      Figure 11.2 Visualizing low‐dimensional data.

      Figure 11.3 2D data set.

      Figure 11.4 First PCA axis.

      Figure 11.5 Second PCA axis.

      Figure 11.6 New axis.

      Figure 11.7 Scatterplot of Royal Dutch Shell stock versus Exxon Mobil stock.

      Figure 12.1 Classification (by quadrant) of earthquakes and explosions using the Chernoff and Kullback–Leibler differences.

      Figure 12.2 Classification (by quadrant) of Lehman Brothers collapse and Flash crash event using the Chernoff and Kullback–Leibler differences.

      Figure 12.3 Clustering results for the earthquake and explosion series based on symmetric divergence using PAM algorithm.

      Figure 12.4 Clustering results for the Lehman Brothers collapse, Flash crash event, Citigroup (2009), and IAG (2011) stock data based on symmetric divergence using the PAM algorithm.

      Figure 13.1 Scatter plot of data in Table 13.1

      Figure 16.1 The

‐plane and several other horizontal planes.

      Figure 16.2 The

‐plane and several parallel planes.

      Figure 16.3 The plane

.

      Figure 16.4 Two class problem when data is linearly separable.

      Figure 16.5 Two class problem when data is not linearly separable.

      Figure 16.6 ROC curve for linear SVM.

      Figure 16.7 ROC curve for nonlinear SVM.

      Figure 17.1 Single hidden layer feed‐forward neural networks.

      Figure 17.2 Simple recurrent neural network.

      Figure 17.3 Long short‐term memory unit.

      Figure 17.4 Philippines (PSI). (a) Basic RNN. (b) LTSM.

      Figure 17.5 Thailand (SETI). (a) Basic RNN. (b) LTSM.

      Figure 17.6 United States (NASDAQ). (a) Basic RNN. (b) LTSM.

      Figure 17.7 JPMorgan Chase & Co. (JPM). (a) Basic RNN. (b) LTSM.

      Figure 17.8 Walmart (WMT). (a) Basic RNN. (b) LTSM.

      Figure 18.1 3D power spectra of the daily returns from the four analyzed stock companies. (a) Discover. (b) Microsoft. (c) Walmart. (d) JPM Chase.

      Figure 18.2 3D power spectra of the returns