Preface |
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vii | |
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1 | (6) |
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Chapter 2 The Abstract Framework |
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7 | (22) |
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2.1 Standard estimation framework |
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7 | (9) |
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2.2 Linear rules that are exact on a subspace |
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16 | (5) |
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2.3 Strong optimality: inner product spaces |
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21 | (5) |
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2.4 Varying the observation |
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26 | (3) |
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Chapter 3 Norm and Kernel of the Remainder Functional |
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29 | (18) |
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3.1 Norm of an estimation rule |
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29 | (4) |
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3.2 The interpolation theorem |
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33 | (3) |
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3.3 Quadrature formulas and one-sided approximation |
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36 | (4) |
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40 | (7) |
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Chapter 4 Co-observations |
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47 | (52) |
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47 | (3) |
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4.2 The Peano kernel theorem |
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50 | (9) |
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4.3 Bounded derivatives as co-observation |
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59 | (4) |
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4.4 Bounded variation as co-observation |
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63 | (3) |
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4.5 Error bounds using the modulus of continuity |
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66 | (6) |
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4.6 Derivatives of bounded variation |
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72 | (1) |
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4.7 Sard's co-observation |
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73 | (3) |
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4.8 Co-observation of Davis type |
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76 | (6) |
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4.9 Bounds in the complex plane as co-observations |
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82 | (11) |
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93 | (6) |
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Chapter 5 Quadrature Rules of Interpolatory Type |
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99 | (50) |
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99 | (5) |
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5.2 The Newton-Cotes method |
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104 | (6) |
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5.3 A theorem of Sloan and Smith |
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110 | (4) |
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5.4 Error bounds for the Clenshaw-Curtis method |
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114 | (7) |
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5.5 Relatives of the Clenshaw-Curtis method |
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121 | (9) |
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5.6 The distribution of nodes |
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130 | (5) |
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5.7 Bounds for the norms of Peano kernels of interpolatory rules |
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135 | (9) |
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5.8 Asymptotic behaviour of a class of Peano kernels |
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144 | (5) |
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Chapter 6 Gaussian Quadrature |
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149 | (62) |
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6.1 Rules of high degree and orthogonal polynomials |
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149 | (7) |
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6.2 Coefficients and nodes for general weights |
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156 | (6) |
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6.3 Nodes and coefficients for w = 1 |
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162 | (4) |
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6.4 Peano kernels for general weights |
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166 | (7) |
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6.5 Peano kernels for w = 1 |
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173 | (7) |
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180 | (9) |
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6.7 Asymptotics of the error |
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189 | (6) |
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6.8 Extremal properties of Gaussian rules |
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195 | (2) |
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6.9 Why Gaussian quadrature? |
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197 | (4) |
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201 | (3) |
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6.11 Kronrod rules for w = 1 |
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204 | (7) |
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Chapter 7 Quadrature Rules with Equidistant Nodes |
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211 | (50) |
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7.1 The trapezoidal method and the Euler-Maclaurin formula |
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211 | (6) |
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7.2 More on the trapezoidal method |
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217 | (13) |
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230 | (3) |
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233 | (3) |
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236 | (8) |
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244 | (10) |
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7.7 Equidistant nodes and the degree of polynomial exactness |
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254 | (2) |
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256 | (5) |
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Chapter 8 Periodic Integrands |
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261 | (30) |
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8.1 The special role of the trapezoidal rule for w = 1 |
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261 | (3) |
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8.2 Error bounds for the trapezoidal rule |
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264 | (7) |
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8.3 Trigonometric interpolation |
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271 | (2) |
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273 | (3) |
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8.5 Standard rules for Fourier coefficients |
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276 | (7) |
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8.6 Other rules for Fourier coefficients |
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283 | (8) |
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Chapter 9 Variance and Chebyshev-type Rules |
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291 | (16) |
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291 | (5) |
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296 | (3) |
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9.3 The special case of w = 1 |
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299 | (4) |
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303 | (4) |
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307 | (8) |
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Appendix A Orthogonal Polynomials |
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315 | (10) |
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Appendix B Bernoulli Polynomials |
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325 | (4) |
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Appendix C Validation of Co-observations |
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329 | (6) |
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C.1 Automatic generation of Taylor coefficients |
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329 | (2) |
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C.2 Real interval arithmetic |
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331 | (2) |
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C.3 Complex interval arithmetic |
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333 | (2) |
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335 | (22) |
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335 | (1) |
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336 | (21) |
Symbols |
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357 | (4) |
Index |
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361 | |