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Johnson N., Kotz S., Kemp A.W. — Univariate discrete distributions
Johnson N., Kotz S., Kemp A.W. — Univariate discrete distributions



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Название: Univariate discrete distributions

Авторы: Johnson N., Kotz S., Kemp A.W.

Аннотация:

Addresses the latest advances in discrete distributions theory including the development of new distributions, new families of distributions and a better understanding of their interrelationships. Greater emphasis on the increasing relevance of Bayesian inference to discrete distribution, especially with regard to the binomial and Poisson distributions, is covered. All chapters have been revised to make them user-friendly and more up-to-date. Extensive information on new mixtures, including generalized hypergeometric families, and the increased use of the computer have been added. The bibliography is updated and expanded along with relevant chapter and section numbers.


Язык: en

Рубрика: Математика/Вероятность/

Статус предметного указателя: Готов указатель с номерами страниц

ed2k: ed2k stats

Издание: second edition

Год издания: 1992

Количество страниц: 568

Добавлена в каталог: 04.06.2005

Операции: Положить на полку | Скопировать ссылку для форума | Скопировать ID
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Предметный указатель
Poisson-related distributions, truncated-Pearson Type III mixed Poissons      332
Poissonian binomial sampling scheme      138—140 152
Polya — Aeppli distribution      88 233 329—330 350 378—382 383 391
Polya — Aeppli distribution, estimation      381—382
Polya — Aeppli distribution, genesis      378
Polya — Aeppli distribution, moment and other properties      380—381
Polynomials: Bell      346—347 430—431
Polynomials: Bernoulli      25 26
Polynomials: Charlier      29
Polynomials: Chebyshev      19 29
Polynomials: Euler      26
Polynomials: Gegenbauer      440
Polynomials: generalized Laguerre      28
Polynomials: Hermite      21—22 27—28
Polynomials: Jacobi      19 29
Polynomials: Krawtchouk      29
Polynomials: Legendre      19
Polynomials: orthogonal      27—29
Power parameter      70
Power series distribution (PSD)      70—77
Power series distribution (PSD), characterizations      71 76—77
Power series distribution (PSD), estimation      73—74 76
Power series distribution (PSD), properties      71—73 75
Probabilities of combined events      33—35 406—409
Probability axioms      33
Probability density function (pdf)      36
Probability mass function (pmf)      36 49
Probleme de rencontre (problem of coincidences)      409—410
Propagation of error      55
Pseudo-binomial variables      147—148 442
q-series distributions: q-binomial      140
q-series distributions: q-logarithmic      304
q-series distributions: q-negative binomial      435
q-series distributions: q-Poisson      197
Queueing theory distributions      98 101 102 106 147 198 203 207 394—395 445 451—453
Random mappings      100
Random variable (rv): continuous      36
Random variable (rv): difference of rv's      50
Random variable (rv): discrete      36
Random variable (rv): sum of rv's      50
Randomly splitting a pack      413
RANGE      51
Rao damage model      174 287 349—350 386 442
Rao — Rubin theorem      174—176 350
Records      453—455
Reed — Frost chain binomial model      104
Regression function      47
Risk function      306
runs      405 422—427
Safety campaign model      464
Sample mean      60
Sample moments      60
Sampling distribution      46
Sampling schemes: binomial      106 152
Sampling schemes: Coolidge      141—142
Sampling schemes: Lexian      141
Sampling schemes: Poisson — Lexis      142
Sampling schemes: Poissonian binomial      138—140 152
Sampling: from finite population      106
Sampling: from infinite population      106
Sampling: imperfect inspection sampling      284
Sampling: inspection sampling      270—271
Sampling: quality control      179 269
Sampling: size-biased      146
Sampling: snowball      104
Sampling: with additional replacements      241 243 245
Sampling: with additional withdrawals      245
Sampling: with replacement      106 418
Sampling: without replacement      134 179 237 241 337 464
Scedasticity      47
SERIES function      70
Sesquimodal      42
Sign test      134
skewness      42
Stable distribution      48
Statistic      57
Statistical physics      405 420—422
Stochastic processes: Arfwedson      204
Stochastic processes: Bernoulli damage      174 349—350
Stochastic processes: birth, death, immigration, and emigration processes      91 106 147 153 180 206—207 224 247—248 287 400 441 445 447 452
Stochastic processes: branching processes      95 147 344 400 441 446 457—458
Stochastic processes: compound Poisson process      356
Stochastic processes: Foster process      198 207
Stochastic processes: mixed Poisson processes      331
Stochastic processes: nonhomogeneous process      154 206 442
Stochastic processes: Poisson process      154 179 180 420
Stochastic processes: Polya process      206 287
Stochastic processes: time-homogeneous process      91
Stochastic processes: Yule — Furry process      287
Stopped-sum distributions      188—189 233 343—403
Stuttering distributions: stuttering negative binomial      363
Stuttering distributions: stuttering Poisson      188 356
Superimposition of distributes      306
Support of a distribution      36
Survival function      36
Symbol: ascending (rising) factorial      2—3
Symbol: binomial coefficient      3
Symbol: descending (falling) factorial      2
Symbol: multinomial coefficient      4
Symbol: Pochhammer's      2
Symbol: q-binomial coefficient      31 434
Symbol: Stirling numbers      10—11
Symbolic calculus      8—9 407
Symbolic representation of mixture      307
Symbolic representation of stopped-sum distributions      344—345
Tails relationships: beta-binomial and beta-negative binomial      254
Tails relationships: binomial and beta (F)      73 117 210
Tails relationships: binomial and negative binomial      209—210 213
Tails relationships: hypergeometric and beta-negative binomial      254—255
Tails relationships: hypergeometric and negative hypergeometric      254—255
Tails relationships: negative binomial and beta      73 209—210
Tails relationships: Poisson and gamma (chi-square)      73 153 160 189—190
Taylor's power law      220 437—438
Theorem of total probability      34
Theory of runs: applications      425
Theory of runs: runs distributions      422—427
Theory of runs: runs of like elements      422—425
Theory of runs: runs up and down      425—426
Theory of runs: success runs distributions      426—427
Theory of runs: total number of runs      423
Theory of runs: turning points      425
Transformations: arc sine (binomial data)      123
Transformations: arc sinh (negative binomial data)      212—213
Transformations: normalizing      55 123 163 212—213
Transformations: square root (Poisson data)      163
Transformations: variance-stabilizing      55 123 163 212—213
Truncation: above (right truncated)      52 184—186 299—300
Truncation: and censoring      53
Truncation: below (left truncated)      52 135—137 181—184 225—227 282
Truncation: double (left and right truncated)      52 136 186
Truncation: points      52
Unidentifiable mixture      310—311
Unimodality      42 327
Unimodality, discrete $\alpha$-unimodality      42
Urn models      134 237 241 245 274 463—465
Urn models, Consul      465
Urn models, Friedman      463—464
Urn models, leaking      417—418
Urn models, Naor      447—448
Urn models, play-the-winner      465
Urn models, Polya      205 245 463 464
Urn models, Rutherford      464—465
Urn models, stochastic replacements      463—465
Urn models, Woodbury      464—465
Vandermonde's theorem      3 17
Variance of a function      54—55
Variance-stabilizing transformation      55 123 163 212—213
Variance-to-mean relationship      228 326 354 437—438
Wald — Wolfowitz two-sample test      425
Weighted distributions      90 94—95 145—147 230—231 248
Whitworth's theorem      409
Wilks' selection problem      447
Zero-modified (inflated/deflated) distributions      186—187 300 312—318
Zero-truncated distributions      135—137 181—183 225—227 282
Zipf — Estoup law      466
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