probability factor function = ϕ(x/µ) = e^(-n*(ln(x/µ)/ln(σ))²)
probability factor function = ϕ(x/µ) = e^(-n*(ln(x/µ)/ln(σ))²)
probability density function = ϕ'(x/µ) = abs(2n*e^(-n*(ln(x/µ)/ln(σ))²)*ln(x)/((ln(σ))^2/x)
project definition ϕ(x/µ)=?
https://sites.google.com/site/scatteringfactordistribution/home/probability-facator-function
question:
ϕ(x/µ)=?
hypothesis:
ϕ(x/µ) = e^(-n*((ln(x/µ))/(ln(σ))²
σ(ϕ) = x(ϕ;n)/µ = σ^±√(-ln(ϕ)/n) = x/µ
x/µ = σ^±√(-ln(ϕ)/n)
x = µ*σ^±√(-ln(ϕ)/n)
x(ϕ;σ;µ;n) = µ*σ^±√(-ln(ϕ)/n)
probability density normal distribution phi'(x/µ) = ϕ'(x/µ)
ϕ'(x/µ) = abs(2n*e^(-n*(ln(x/µ)/ln(σ))²)*ln(x)/((ln(σ))^2/x)
test:
monte carlo simulation excel N = 10000
excel random generator probability factor normal distribution sigma zeta phi deisenroth
x(ϕ)/µ = ?
x(ϕ)/µ = σ^±√(-ln(ϕ)
= σ^(((GANZZAHL((EXP(LN((0,5+ZUFALLSZAHL())))))-0,5)*2)*((-LN(ZUFALLSZAHL()))^0,5)^(1^0,5))
ϕ(x/µ) = probability factor phi deisenroth
probability factor sigma deisenroth
σ(ϕ) = probability factor sigma deisenroth = x(ϕ)/µ
probability factor normal distribution sigma zeta phi deisenroth
σ(ϕ;n) = σ^(±ζ(ϕ)/n^0,5) = x(ϕ;n)/µ
σ(ϕ;n)= σ^(±√((-ln(ϕ)/n))) = x(ϕ;n)/µ
ϕ(x;n) = e^(-n*((ln(x/µ))/(ln(σ))²)
x(ϕ;n) = µ∗σ^(±√((-ln(ϕ)/n)))
ϕ(σ;n) = e^(-n*((ln(x(ϕ;n)/µ))/(ln(σ))²)
ζ(ϕ) = ±√(-ln(ϕ))
ζ(ϕ;n) = ±√(-ln(ϕ)/n)
true arithmetic mean (µari) and true geometric mean (µgeo or µ)
µari = true arithmetic mean (wahrer arithmetischer mittelwert)
µgeo or µ = true geometric mean (wahrer geometrischer mittelwert)
estimated arithmetic mean (xari) and estimated geometric mean (xgeo)
xari = estimated arithmetic mean (geschätzter arithmetischer mittelwert)
xgeo = estimeted geometric mean (geschätzter geometrischer mittelwert)
xgeo(xi;n) = e^(1/n*((ln(x1)+ln(x2)+.....+ln(xn)))
xgeo(sdi;n) = xari/e^(0,5*ln(sd)^2)
probability limit base sigma deisenroth
probability factor phi deisenroth
σ(µari/µ) = e^(2∗ln(µari/µ))^0¸5
standard probability limit base sigma deisenroth
standard probability limit factor sigma deisenroth
σ(µari/µ) = e^(2∗ln(µari/µ))^0¸5
standard probability limit exponent zeta deisenroth
ζ(ϕ=0,368) = 1
standard probability limit factor phi deisenroth
ϕ(ζ=1) = e^-ζ² = e^-1² = 0,368
standard sigma deisenroth
σ(µari/µ) = e^(2∗ln(µari/µ))^0¸5
standard zeta deisenroth
ζ(ϕ=0,368) = 1
standard phi deisenroth
ϕ(ζ=1) = e^-ζ² = e^-1² = 0,368
confidence limit base deisenroth
σ(µari/µ) = e^(2∗ln(µari/µ))^0¸5
confidence limit factor sigma deisenroth
σ(ϕ;n) = σ^(±ζ(ϕ)/n^0,5)
confidence limit exponent zeta deisenroth
ζ(ϕ) = ±√(-ln(ϕ))
σ(µari/µ) = e^(2∗ln(µari/µ))^0¸5
confidence limit factor phi deisenroth
ϕ(σ;n) = e^(-n*((ln(x(ϕ;n)/µ))/(ln(σ))²)
standard confidence limit factor sigma deisenroth
σ(µari/µ) = e^(2∗ln(µari/µ))^0¸5
standard confidence limit exponent zeta deisenroth
ζ(ϕ=0,368) = 1
standard confidence limit factor phi deisenroth
ϕ(ζ=1) = e^-ζ² = e^-1² = 0,368
development sigma zeta phi score
for
true standard probability factor sigma deisenroth σ
true confidence limit factor sigma deisenroth σ(ϕ)
true confidence limit exponent zeta deisenroth ζ(ϕ)
true probability phi deisenroth ϕ(x)
© Frank Deisenroth, Alle Rechte vorbehalten.