53 lines
1.4 KiB
Go
53 lines
1.4 KiB
Go
package main
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import "fmt"
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import "math"
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import rand "math/rand/v2"
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var r = rand.New(rand.NewPCG(1, 2))
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func sample_unit_uniform() float64 {
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return r.Float64()
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}
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func sample_unit_normal() float64 {
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return r.NormFloat64()
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}
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func sample_uniform(start float64, end float64) float64 {
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return sample_unit_uniform()*(end-start) + start
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}
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func sample_normal(mean float64, sigma float64) float64 {
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return mean + sample_unit_normal()*sigma
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}
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func sample_lognormal(logmean float64, logstd float64) float64 {
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return (math.Exp(sample_normal(logmean, logstd)))
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}
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func sample_normal_from_90_ci(low float64, high float64) float64 {
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var normal90 float64 = 1.6448536269514727
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var mean float64 = (high + low) / 2.0
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var std float64 = (high - low) / (2.0 * normal90)
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return sample_normal(mean, std)
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}
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func sample_to(low float64, high float64) float64 {
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// Given a (positive) 90% confidence interval,
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// returns a sample from a lognorma with a matching 90% c.i.
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// Key idea: If we want a lognormal with 90% confidence interval [a, b]
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// we need but get a normal with 90% confidence interval [log(a), log(b)].
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// Then see code for sample_normal_from_90_ci
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var loglow float64 = math.Log(low)
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var loghigh float64 = math.Log(high)
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return math.Exp(sample_normal_from_90_ci(loglow, loghigh))
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}
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func main() {
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fmt.Println("Hello world!")
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fmt.Printf("%v\n", r.Float64())
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fmt.Printf("%v\n", r.NormFloat64())
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}
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