inverse distribution function

  • 21Dirac delta function — Schematic representation of the Dirac delta function by a line surmounted by an arrow. The height of the arrow is usually used to specify the value of any multiplicative constant, which will give the area under the function. The other convention… …

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  • 22Exponential distribution — Not to be confused with the exponential families of probability distributions. Exponential Probability density function Cumulative distribution function para …

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  • 23Negative binomial distribution — Probability mass function The orange line represents the mean, which is equal to 10 in each of these plots; the green line shows the standard deviation. notation: parameters: r > 0 number of failures until the experiment is stopped (integer,… …

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  • 24Multivariate normal distribution — MVN redirects here. For the airport with that IATA code, see Mount Vernon Airport. Probability density function Many samples from a multivariate (bivariate) Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the… …

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  • 25Chi-squared distribution — This article is about the mathematics of the chi squared distribution. For its uses in statistics, see chi squared test. For the music group, see Chi2 (band). Probability density function Cumulative distribution function …

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  • 26Maxwell–Boltzmann distribution — Maxwell–Boltzmann Probability density function Cumulative distribution function parameters …

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  • 27Noncentral t-distribution — Noncentral Student s t Probability density function parameters: degrees of freedom noncentrality parameter support …

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  • 28Noncentral chi-squared distribution — Noncentral chi squared Probability density function Cumulative distribution function parameters …

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  • 29von Mises distribution — von Mises Probability density function The support is chosen to be [ π,π] with μ=0 Cumulative distribution function The support is chosen to be [ π,π] with μ=0 …

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  • 30Geometric stable distribution — Geometric Stable parameters: α ∈ (0,2] stability parameter β ∈ [−1,1] skewness parameter (note that skewness is undefined) λ ∈ (0, ∞) scale parameter μ ∈ (−∞, ∞) location parameter support: x ∈ R, or x ∈ [μ, +∞) if α < 1 and β = 1, or x ∈… …

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