An introduction to L1-norm based statistical data analysis

Computational Statistics and Data Analysis

Volumn 5, Issue 4, 1987, Pages 239-253

  Dodge, Yadolah ^a  

^a UNIVERSITY OF NEUCHÂTEL   (Switzerland)

Author keywords

L1 norm; Least absolute deviations estimation; Linear programming; Minimum absolute deviations; Minimum sum of absolute errors

Indexed keywords

EID: 38249034009     PISSN: 01679473     EISSN: None     Source Type: Journal    
DOI: 10.1016/0167-9473(87)90048-X     Document Type: Article

References (98)

1. 1 solution of overdetermined systems of linear equations,
2. A robust method for multiple linear regression
3. A special purpose linear programming algorithm for obtaining least absolute value estimates in a linear model with dummy variables
4. 1 norm
5. AS132 Least absolute value estimates for a simple linear regression problem
6. Obtaining least absolute value estimates for a two-way classification model
7. A revised simplex algorithm for the absolute deviation curve fitting problem
8. A sampling study of minimum absolute deviations estimators
9. 1 linear approximation
10. 1 norm
11. 1 linear approximation with linear constraints
12. LAV regression A special case of piecewise linear minimization
13. 1 solution to an overdetermined linear system
14. Asymptotic theory of least absolute error
15. One-step Huber estimates in the linear model
16. Least absolute deviations curve-fitting
17. De litteraria expeditione per pontificiam ditionem, et synopsis amplioris operis ac habentur plura eius ex exemplaria etiam sensorum impressa
18. A Monte Carlo sampling study for further testing of the robust regression procedure based upon the kurtosis of the least squares residuals
19. Non-normality and tests on variances
20. Optimal estimation of executive compensation by linear programming
21. 1 for kernel density estimates
22. Least absolute value estimation in regression models An annotated bibliography
23. LAV (least absolute value) estimation in linear regression:
24. Some difficulties involving nonparametric estimation of a density function
25. Adaptive combination of least squares and least absolute deviations estimators
26. A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters
27. 1-estimates of regression
28. On observations relating to several quantities
29. p- or Huber-estimate
30. 2 problems
31. ∞ estimation procedures, in
32. Various discrepancy measures in model testing (two competing regression models
33. Numerical techniques for finding estimates which minimize the upper bound of the absolute deviation
34. Least absolute values estimation An introduction
35. 1 linear regression
36. The small sample properties of simultaneous equation least absolute estimators vis-vis least squares estimators
37. 1-norm estimation problems
38. p-norm estimation
39. Density estimation from dependent sample
40. Contributions to the theory of robust estimation
41. A general qualitative definition of robustness
42. The method of least squares and some alternatives I
43. The method of least squares and some alternatives II
44. The method of least squares and some alternatives III
45. The method of least squares and some alternatives IV
46. The method of least squares and some alternatives IV
47. The method of least squares and some alternatives V
48. The method of least squares and some alternatives VI
49. Robust estimation of a location parameter
50. Robust statistics A review
51. Robust regression Asymptotics conjectures and Monte Carlo
52. 1-norm in robust estimation
53. A dynamic programming algorithms for cluster analysis
54. 1-norm estimates for the simple regression problem
55. Linear curve fitting using least deviations
56. Clustering by means of medoids
57. A polynomial algorithm for linear programming
58. Linear programming techniques in regression analysis
59. 1-regression
60. 1 estimation
61. Sur quelques points du systéme du montde
62. [Introduction to clinical practice of a 1st-year student by a 2d-year student].
63. Least absolute errors analysis of variance
64. The minimum sum of absolute errors regression
65. The reduced gradient algorithm
66. On the estimation of a probability density function and the mode
67. Absolute deviations curve fitting: An Alternative to Least Squares
68. Reducing observations by the method of minimum deviations
69. Norms for smoothing and estimation
70. P-norm estimators in a linear regression model
71. Asymptotic normality of p-norm estimators in multiple regression
72. A simple approximation of the sampling distribution of least absolute residuals regression estimates
73. 1 to astronomy
74. Small sample properties of least absolute errors analysis of variance
75. Two linear programming algorithms for unbiased estimation of linear models
76. A method of minimizing the sum of absolute values of deviations
77. 1 norm within cluster analysis
78. 1 regression
79. Studies in the history of probability and statistics, XXXII: Laplace, Fisher, and the discovery of sufficiency
80. Gauss and the invention of least squares
81. Estimation by minimizing the sum of absolute errors
82. 1 in fuzzy clustering
83. On Mr Edgeworth's method of reducing observations relating to several quantities
84. 1-distances in statistical inference: Comparison of topological, functional and statistical properties
85. Integer programming and theory of grouping
86. Linear programming techniques for regression analysis
87. Least squares versus minimum absolute deviations estimation in linear models