Isbn: 9786131753268 - inverse transform sampling: vladimir ivanovich smirnov (mathematician), random, probability distribution, cumulative distribution function, inverse function (4 resultados)

ISBN: 
Refinar con la Búsqueda avanzada

Filtrar la búsqueda

  • Libros (4)

  • Nuevo (4)

a

Intervalo de precios personalizado (EUR)

a

  • Idioma: Inglés

    Editorial: Omniscriptum Mär 2026, 2026

    6131753261 / 9786131753268

    • Tapa blanda
    • Impresión bajo demanda

    Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, AlemaniaBuchWeltWeit Ludwig Meier e.K.

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 136,00

    Envío por EUR 23,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 76 pp. Englisch.

  • Idioma: Inglés

    Editorial: Omniscriptum, 2010

    6131753261 / 9786131753268

    • Tapa blanda
    • Impresión bajo demanda

    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 137,63

    Envío por EUR 35,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. Inverse transformsampling, also known as the inverse probability integral transform orinverse transformation method or Smirnov transform, is a method forgenerating sample numbers at random from any probability distributiongiven its cumulative distribution function (cdf). Subject to therestriction that the distribution is continuous, this method isgenerally applicable (and can be computationally efficient if the cdfcan be analytically inverted), but may be too computationally expensivein practice for some probability distributions. The Box-Muller transformis an example of an algorithm that is specific to generating samplesfrom a normal distribution, but is more computationally efficient. It isoften the case that, even for simple distributions, the inversetransform sampling method can be improved on: see, for example, theziggurat algorithm and rejection sampling.…

  • Idioma: Inglés

    Editorial: OmniScriptum, 2026

    6131753261 / 9786131753268

    • Tapa blanda
    • Impresión bajo demanda

    Librería: preigu, Osnabrück, Alemaniapreigu

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 109,85

    Envío por EUR 70,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Inverse Transform Sampling | Vladimir Ivanovich Smirnov (mathematician), Random, Probability distribution, Cumulative distribution function, Inverse function | Frederic P. Miller (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786131753268 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…

  • Idioma: Inglés

    Editorial: Omniscriptum Mär 2026, 2026

    6131753261 / 9786131753268

    • Tapa blanda
    • Impresión bajo demanda

    Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemaniabuchversandmimpf2000

    Vendedor de 5 estrellas
    Contactar con el vendedor

    Condición: Nuevo

    EUR 136,00

    Envío por EUR 60,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 1 disponible

    Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. Inverse transformsampling, also known as the inverse probability integral transform orinverse transformation method or Smirnov transform, is a method forgenerating sample numbers at random from any probability distributiongiven its cumulative distribution function (cdf). Subject to therestriction that the distribution is continuous, this method isgenerally applicable (and can be computationally efficient if the cdfcan be analytically inverted), but may be too computationally expensivein practice for some probability distributions. The Box-Muller transformis an example of an algorithm that is specific to generating samplesfrom a normal distribution, but is more computationally efficient. It isoften the case that, even for simple distributions, the inversetransform sampling method can be improved on: see, for example, theziggurat algorithm and rejection sampling.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch.…