1.5 KiB
1.5 KiB
sidebar_position |
---|
1 |
Squiggle Language
Distributions
normal(a,b)
uniform(a,b)
lognormal(a,b)
lognormalFromMeanAndStdDev(mean, stdev)
beta(a,b)
exponential(a)
triangular(a,b,c)
mm(a,b,c, [1,2,3]) //todo: change to mix, or mx(). Also, change input format, maybe to mx([a,b,c], [a,b,c]).
cauchy() //todo
pareto() //todo
metalog() //todo
Functions
pdf(distribution, float)
inv(distribution, float)
cdf(distribution, float)
mean(distribution)
sample(distribution)
scaleExp(distribution, float)
scaleMultiply(distribution, float)
scaleLog(distribution, float)
samples(distribution, n) //todo
toPdf(distribution) //todo
toCdf(distribution) //todo
toHash(distribution) //todo. Make hash of content, like, {xs:[], ys:[]}
trunctate(distribution, leftValue, rightValue) //todo
leftTrunctate(distribution, leftValue) //todo
rightTrunctate(distribution, rightValue) //todo
distributionFromSamples(array, params) //todo
distributionFromPoints() //todo
distributionFromHash() //todo
Example Functions
ozzie_estimate(t) = lognormal({mean: 3 + (t+.1)^2.5, stdev: 8})
nuño_estimate(t) = lognormal({mean: 3 + (t+.1)^2, stdev: 10})
combined(t) = mm(ozzie_estimate(t) .+ nuño_estimate(t))
combined
us_economy_2018 = (10.5 to 10.9)T
growth_rate = 1.08 to 1.2
us_economy(t) = us_economy_2018 * (growth_rate^t)
us_population_2019 = 320M to 330M
us_population_growth_rate = 1.01 to 1.1
us_population(t) = us_population_2019 * (us_population_growth_rate^t)
gdp_per_person(t) = us_economy(t)/us_population(t)
gdp_per_person
gdp_per_person