前辅文
 Part I Geometry
  1 Preliminaries
   1.1 Linear algebra
    1.1.1 Vectors and matrices
    1.1.2 Symmetric bilinear forms
    1.1.3 Vector subspaces
    1.1.4 Linear maps from Rn to Rn
    1.1.5 A convention
   1.2 Vector calculus
    1.2.1 Vector-valued functions and differentials
    1.2.2 Taylor expansion and extrema
    1.2.3 Extrema and Lagrange multiplier theorem
  2 Euclidean Geometry
   2.1 Orthogonal transformations
   2.2 Rigid motions
   2.3 Translation of vector subspaces
   2.4 Conformal transformations
   2.5 Orthonormal basis
   2.6 Orthogonal projections
   2.7 Areas and volumes
  3 Geometry of Graphs
   3.1 Graphs in Euclidean spaces
   3.2 Normal sections
   3.3 Cross sections in high dimension
   3.4 First fundamental forms
  4 Curvatures
   4.1 Normal curvatures
    4.1.1 Definition
    4.1.2 Principal curvatures and principal directions
   4.2 Sectional curvatures
  5 Transformations and Invariance
   5.1 Change of coordinates
   5.2 Non-linear conformal transformations
   5.3 Invariant curvatures
 Part II Statistics
  6 Discrete Random Variables and Related Concepts
   6.1 Preliminaries
   6.2 Discrete random variables
    6.2.1 Discrete random variables and probability function
    6.2.2 Relative frequency histogram
    6.2.3 Cumulative distribution function
   6.3 Population parameters and sample statistics
    6.3.1 Population mean and expected value
    6.3.2 Sample statistic
    6.3.3 Sample mean
    6.3.4 Sample and population variances
   6.4 Mathematical expectations
   6.5 Maximum likelihood estimation
   6.6 Maximum likelihood estimation of the probability of a Bernoulli experiment
  7 Continuous Random Variables and Related Concepts
   7.1 Continuous random variables
   7.2 Mathematical expectation for continuous random variables
   7.3 Mean and variance and their sample estimates
   7.4 Basic properties of expectations
   7.5 Normal distribution
   7.6 Maximum likelihood estimation for continuous variables
   7.7 Maximum likelihood estimation for the parameters of normal distribution
   7.8 Sampling distribution
  8 Bivariate and Multivariate Distribution
   8.1 Bivariate distribution for discrete random variables
    8.1.1 Joint probability function
    8.1.2 Marginal probability function
    8.1.3 Conditional probability function
   8.2 Bivariate distribution for continuous random variables
   8.3 Mathematical expectations
    8.3.1 Mathematical expectations for the functions of two random variables
   8.4 Covariance and correlation
    8.4.1 Sample covariance and correlation
    8.4.2 Population covariance and correlation
    8.4.3 Conditional expectations
   8.5 Bivariate normal distribution
   8.6 Independence
   8.7 Multivariate distribution
  9 Simple Linear Regression
   9.1 The model
   9.2 The least squares estimation
   9.3 The maximum likelihood estimation of regression parameters
   9.4 Residuals
   9.5 Coefficient of determination
   9.6 Weighted least squares estimates
  10 Topics on Linear Regression Analysis
   10.1 Multiple regression model
   10.2 Estimation and interpretation
   10.3 Influential observations and outliers
   10.4 Leverage
   10.5 Cook's distance
   10.6 Deletion influence, joint influence and masking effect
   10.7 Derivation of Cook's distances
    10.7.1 Weighted least squares and Cook's distance
    10.7.2 Cook's distance-deleting one data point
 Part III Local Influence Analysis
  11 Basic Concepts
   11.1 Introduction
   11.2 Perturbation
   11.3 Likelihood displacement and influence graph
  12 Measuring Local Influence
   12.1 Individual influence
   12.2 Derivation of normal curvature
   12.3 Case-weight perturbation—an example
   12.4 Roles of sectional curvature
   12.5 Joint influence
  13 Relations Among Various Measures
   13.1 A bound on influence measures
   13.2 Individual and overall joint influence
   13.3 Individual and joint influence measures
   13.4 Competing eigenvalues
   13.5 Conclusions
  14 Conformal Modifications
   14.1 Modification and invariance
   14.2 Invariant measures
   14.3 Benchmarks
   14.4 Individual's contribution to joint influence—re-visited
 Appendix A Rank of Hat Matrix
 Appendix B Ricci Curvature
 Appendix C Cook's Distance—Deleting Two Data Points
 Bibliography
 Index