Pollard D. — Convergence of Stochastic Processes :: Электронная библиотека попечительского совета мехмата МГУ

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Pollard D. — Convergence of Stochastic Processes

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Название: Convergence of Stochastic Processes

Автор: Pollard D.

Язык:

Рубрика: Математика/Вероятность/Стохастические процессы/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Год издания: 1984

Количество страниц: 215

Добавлена в каталог: 16.12.2004

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID

Предметный указатель

Poisson process      105 129
Pollard, D.      36—39 118 166 169
Polynomial, bound for number of sets picked out      19
Polynomial, class      17 27
Polynomial, discriminating      17
Polynomial, discrimination      17 20
Polynomial, orthogonal      47
Predictable      176
Product $\sigma$ -field      69
Prohorov, Yu. V.      85-.86
Prohorov’s theorem      See “Compactness Theorem”
Projection $\sigma$ -field      66 90
Projection $\sigma$ -field on $D[0,\infty)$       127
Projection $\sigma$ -field on D[0,1]      87
Projection maps      66 90
Projection maps for $D[0,\infty)$       130
Projection, measurability of      196
Pyke, R.      vii 85—86 167
Quadratic variation process      185
Quantile transformation      57 97 129
Random element of metric space      1 65
Random vector, characteristic functions      56
Random vector, convergence in distribution of      43 56
Random vector, perturbation of      48
Ranga Rao, R.      86
Rates of convergence      30
Reflection principle, for brownian motion      112
Remainder term in Taylor expansion      50 139
Representation Theorem with random elements      71
Representation Theorem with random variables      58
Resnick, S. I.      136
Revesz, P.      118 167
Robustnik      75
Sample path      1
Sauer, N.      37
Scheffe’s lemma      61
Semicontinuity      73 87
Seminorm      xiv
Separability and $\sigma$ -fields      85
Separability for subsets of metric spaces      67
Separability of $D[0,\infty)$ , under Skorohod metric      127
Separability of C[0,1]      87
Separability, universal      38
Shatter      18 21 198
Shelah, S.      37
Shiryayev, A. N.      185
Shorack, G.      vii—viii 85
Sigma field      See “ $$\mathcal{B}^P</a></span> <span class=subjpages><a href=$
Sigma field, generated by balls      87
Sign variables      15
Signed measure      See “ $P^\circ_n$ ”
Silverman, B. W.      38
Simmons, G. F.      67—68 85
Skorohod, A. V.      4 86 117—118 122 136—137 166 185
Slutsky’s theorem      62
Souslin      196
Square-root trick      32 37
Steele, J. M.      37
Stirling’s approximation      21

Stochastic equicontinuity      139—140
Stochastic order symbol      141 189
Stochastic process      1
Stone, C.      118 136
Stopping time      110 172
Straf, M.      136
Strasbourg theory      176
Strassen, V.      86 167
Strong markov property, for brownian motion      111
Stute, W.      vii 36—38 117
Submartingale      178
Submartingale, reversed      22 25
Subsets, hidden      19
Subsets, picked out      18
Substitution, of increments      49
Sun, T. G.      167
Symmetrization      32 149
Symmetrization Lemma      14 198
Symmetrization, First      14
Symmetrization, inequality      14—15
Symmetrization, Second      15
Symmetry and empirical measures      21
Tail probability, characteristic function bound      60
Tail probability, exponential bound      160
Tail probability, tied-down brownian motion      See “Brownian bridge”
Talagrand, M.      85
Tight measure on metric space      81
Tight measure on real line      60
Tong, Y. L.      41
Topsoe, F.      36—37 62 85—86
Total boundedness and P-motion      168
Total boundedness of metric space      82
Triangular array      51 106
Troallic, J. P.      86
Truncation      25
Uniform convergence of density estimator      36
Uniform integrability      176
Uniform strong law of large numbers      7
Uniform strong law of large numbers for classes of functions      25 168
Uniform strong law of large numbers for classes of sets      18 22
Uniform strong law of large numbers for convex sets      22
Uniform tightness for general empirical processes      156
Uniform tightness for uniform empirical processes      102
Uspensky, J. V.      61 193
Usual conditions      176
Vapnik, V. N.      37
Varadarajan, V. S.      85
VC class      37
Vector space, finite-dimensional      20 30 38
Wald, A.      189
Weak convergence in euclidean space      44
Weak convergence in metric spaces      65
Weierstrass, K.      61
Weight functions      158
Wellner, J.      viii
Whitt,W.      118
Wichura, M.      86
Yu, K. F.      186
Zinn, J.      37 38 40 166—167

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