Generalized Gaussian Error Calculus / Edition 1

Generalized Gaussian Error Calculus / Edition 1

by Michael Grabe
ISBN-10:
3642033040
ISBN-13:
9783642033049
Pub. Date:
02/19/2010
Publisher:
Springer Berlin Heidelberg
ISBN-10:
3642033040
ISBN-13:
9783642033049
Pub. Date:
02/19/2010
Publisher:
Springer Berlin Heidelberg
Generalized Gaussian Error Calculus / Edition 1

Generalized Gaussian Error Calculus / Edition 1

by Michael Grabe

Hardcover

$109.99 Current price is , Original price is $109.99. You
$109.99 
  • SHIP THIS ITEM
    Qualifies for Free Shipping
  • PICK UP IN STORE
    Check Availability at Nearby Stores

Overview

For the first time in 200 years Generalized Gaussian Error Calculus addresses a rigorous, complete and self-consistent revision of the Gaussian error calculus. Since experimentalists realized that measurements in general are burdened by unknown systematic errors, the classical, widespread used evaluation procedures scrutinizing the consequences of random errors alone turned out to be obsolete. As a matter of course, the error calculus to-be, treating random and unknown systematic errors side by side, should ensure the consistency and traceability of physical units, physical constants and physical quantities at large.

The generalized Gaussian error calculus considers unknown systematic errors to spawn biased estimators. Beyond, random errors are asked to conform to the idea of what the author calls well-defined measuring conditions.

The approach features the properties of a building kit: any overall uncertainty turns out to be the sum of a contribution due to random errors, to be taken from a confidence interval as put down by Student, and a contribution due to unknown systematic errors, as expressed by an appropriate worst case estimation.


Product Details

ISBN-13: 9783642033049
Publisher: Springer Berlin Heidelberg
Publication date: 02/19/2010
Edition description: 2010
Pages: 301
Product dimensions: 6.10(w) x 9.20(h) x 0.90(d)

About the Author

1967 Graduation in Physics at the Technical University of Stuttgart

1970 Doctorate at the Technical University of Braunschweig

1970 – 1975 Scientific assistant and lecturer at the Technical University of Braunschweig

1975 – 2004 Member of Staff at the Physikalische Technischer Bundesanstalt Braunschweig, commissioned to legal metrology, computerized interferometric measurment of length, measurement uncertainties and the adjustment of physical constants

Table of Contents

Part I Basics of Metrology

1 True Values and Traceability 3

1.1 Metrology 3

1.2 Traceability 3

1.3 Measurement Errors 4

1.4 Precision and Accuracy 6

1.5 Measurement Uncertainty 6

1.6 Measuring Result 6

1.7 Rivaling Physical Approaches 8

2 Models and Approaches 9

2.1 Gaussian Error Model 9

2.2 Generalized Gaussian Approach 10

2.3 Robust Testing Conditions 14

2.4 Linearizations 15

2.5 Quiddity of Least Squares 16

2.6 Analysis of Variance 20

2.7 Road Map 21

Part II Generalized Gaussian Error Calculus

3 The New Uncertainties 25

3.1 Gaussian Versus Generalized Gaussian Approach 25

3.2 Uncertainty and True Value 25

3.3 Designing Uncertainties 26

3.4 Quasi Safeness 29

4 Treatment of Random Errors 31

4.1 Well-Defined Measuring Conditions 31

4.2 Multidimensional Normal Model 32

4.3 Permutation of Repeated Measurements 33

5 Treatment of Systematic Errors 35

5.1 Repercussion of Biases 35

5.2 Uniqueness of Worst-Case Assessments 36

Part III Error Propagation

6 Means and Means of Means 39

6.1 Arithmetic Mean 39

6.2 Extravagated Averages 41

6.3 Mean of Means 41

6.4 Individual Mean Versus Grand Mean 47

7 Functions of Erroneous Variables 53

7.1 One Variable 53

7.2 Two Variables 56

7.3 More Than Two Variables 61

7.4 Concatenated Functions 66

7.5 Elementary Examples 68

7.6 Test of Hypothesis 74

8 Method of Least Squares 79

8.1 Empirical Variance-Covariance Matrix 79

8.2 Propagation of Systematic Errors 82

8.3 Uncertainties of the Estimators 83

8.4 Weighting Factors 84

8.5 Example 87

Part IV Essence of Metrology

9 Dissemination of Units 91

9.1 Working Standards 91

9.2 Key Comparisons 95

10 Multiples and Sub-multiples 101

10.1 Calibration Chains 101

10.2 Pairwise Comparisons 110

11 Founding Pillars 113

11.1 Consistency 113

11.2 Traceability 114

Part V Fitting of Straight Lines

12 Preliminaries 117

12.1 Distinction of Cases 117

12.2 True Straight Line 118

13 Straight Lines: Case (i) 121

13.1 Fitting Conditions 121

13.2 Orthogonal Projection 121

13.3 Uncertainties of the Input Data 123

13.4 Uncertainties of the Components of the Solution Vector 124

13.5 Uncertainty Band 126

13.6 EP-Region 127

14 Straight Lines: Case (ii) 131

14.1 Fitting Conditions 131

14.2 Orthogonal Projection 132

14.3 Uncertainties of the Components of the Solution Vector 132

14.4 Uncertainty Band 135

14.5 EP-Region 137

15 Straight Lines: Case (iii) 141

15.1 Fitting Conditions 141

15.2 Orthogonal Projection 142

15.3 Series Expansion of the Solution Vector 143

15.4 Uncertainties of the Components of the Solution Vector 145

15.5 Uncertainty Band 147

15.6 EP-Region 148

Part VI Fitting of Planes

16 Preliminaries 155

16.1 Distinction of Cases 155

16.2 True Plane 155

17 Planes: Case (i) 157

17.1 Fitting Conditions 157

17.2 Orthogonal Projection 157

17.3 Uncertainties of the Input Data 158

17.4 Uncertainties of the Components of the Solution Vector 159

17.5 EPC-Region 161

18 Planes: Case (ii) 165

18.1 Fitting Conditions 165

18.2 Orthogonal Projection 166

18.3 Uncertainties of the Components of the Solution Vector 166

18.4 Confidence Intervals and Overall Uncertainties 168

18.5 Uncertainty Bowls 169

18.6 EPC-Region 171

19 Planes: Case (iii) 179

19.1 Fitting Conditions 179

19.2 Orthogonal Projection 180

19.3 Series Expansion of the Solution Vector 181

19.4 Uncertainties of the Components of the Solution Vector 183

19.5 Uncertainty Bowls 185

19.6 EPC-Region 187

Part VII Fitting of Parabolas

20 Preliminaries 193

20.1 Distinction of Cases 193

20.2 True Parabola 193

21 Parabolas: Case (i) 195

21.1 Fitting Conditions 195

21.2 Orthogonal Projection 195

21.3 Uncertainties of the Input Data 196

21.4 Uncertainties of the Components of the Solution Vector 197

21.5 Uncertainty Band 199

21.6 EPC-Region 199

22 Parabolas: Case (ii) 203

22.1 Fitting Conditions 203

22.2 Orthogonal Projection 294

22.3 Uncertainties of the Components of the Solution Vector 204

22.4 Uncertainty Band 207

22.5 EPC-Region 209

23 Parabolas: Case (iii) 213

23.1 Fitting Conditions 213

23.2 Orthogonal Projection 214

23.3 Series Expansion of the Solution Vector 215

23.4 Uncertainties of the Components of the Solution Vector 217

23.5 Uncertainty Band 219

23.6 EPC-Region 220

Part VIII Non-linear Fitting

24 Series Truncation 227

24.1 Homologous True Function 227

24.2 Fitting Conditions 228

24.3 Orthogonal Projection 228

24.4 Iteration 230

24.5 Uncertainties of the Components of the Solution Vector 231

25 Transformation 237

25.1 Homologous True Function 237

25.2 Fitting Conditions 237

25.3 Orthogonal Projection 238

25.4 Uncertainties of the Components of the Solution Vector 239

Part IX Appendices

A Graphical Scale Transformations 245

B Expansion of Solution Vectors 251

C Special Confidence Ellipses and Ellipsoids 257

D Extreme Points of Ellipses and Ellipsoids 261

E Drawing Ellipses and Ellipsoids 265

F Security Polygons and Polyhedra 267

G EP Boundaries and EPC Hulls 277

H Student's Density 283

I Uncertainty Band Versus EP-Region 287

J Quantiles of Hotelling's Density 295

References 297

Index 299

From the B&N Reads Blog

Customer Reviews