# Simple calculations

Gamma function: Γ()

# Distributions for Bernoulli processers

### Binomial distribution: bin(n,p)(x)

Plot probability distribution: n= , p=
Point probability, bin, bin: n= , p= , x=
Cumulative probability, BIN: n= , p= , x=

### Negative binomial distribution: nb(k,p)(x)

Plot of probability distribution: k= , p=
Point probability, nb: k= , p= , x=
Cumulative probability, NB: k= , p= , x=

### β distribution: β(a,b)(x)

Plot of probability distribution: a=, b=
Cumulative probability, I: a= , b=, x=
Inverse cumulative probability, I-1: a= , b=, p=

### Beta-binomial distribution: βb(a,b,n)(x)

Plot of probability distribution: a=, b=, n=
Point probability, βb: a=, b=, n=, x=
Cumulative probability, BB: a=, b=, n=, x=

### Beta negative binomial distribution: βnb(a,b,k)(x)

Plot of probability distribution: a=, b=, k=
Point probability, βnb: a=, b=, k=, x=
Cumulative probability, BNB: a=, b=, k=, x=

# Distributions for Poisson processes

### Poisson distribution: poisλ(x)

Plot of probability distribution: λ=
Point probability, pois: λ=, x=
Cumulative probability, POIS: λ= , x=

### Gamma distribution: γ(k,λ)(x)

(special forms are Erlang, Eksponential and χ2 distribution)

Plot of probability distribution: k=, λ=
Cumulative calculations, Γ: k=, λ=, t=
Cumulative calculations, Γ-1: k= , λ=, p=

### Gamma-gamma distribution: gγ(k,κ,λ)(x)

(also known as the Beta II distribution)

Plot of probability distribution: k=, κ=, λ=
Cumulative calculations, GΓ: k=, κ=, λ=, t=

### Negative binomial distribution: nb(k,p)(x)

Plot of probability distribution: k= , p=
Point probability, nb: k= , p= , x=
Cumulative probability, NB: k= , p= , x=

# Gaussian processes

### Normal distribution: φ(μ,σ)(x)

(the notation N is often used instead of φ)

Plot of probability distribution: μ=, σ=
Cumulative calculations, Φ: μ= , σ=, x=
Inverse cumulative calculations, Φ-1: μ= , σ=, p=

### Gamma distribution: γ(k,λ)(x)

(the special form χ2 is often used for gaussian processes)

Plot of probability distribution: k=, λ=
Cumulative calculations, Γ: k=, λ=, t=
Inverse cumulative calculations, Γ-1: k= , λ=, p=

### Student's t distribution: t(μ,σ,ν)(x)

Plot of probability distribution: μ=, σ=, ν=
Cumulative calculations, T: μ= , σ=, ν=, x=
Inverse cumulative calculations, T-1: μ= , σ=, ν=, p=

# Other distributions

### Weibull-fordeling: weib(k,λ)(x)

Plot of probability distribution: k= , λ=
Cumulative calculations, WEIB: k= , λ=, x=
Inverse cumulative calculations, WEIB-1: k=, λ=, p=