Minor changes
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@ -11,7 +11,7 @@ let logNormal = (mean: float, std: float) => {
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Js.Float.(
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{
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let nMean = toPrecisionWithPrecision(Js.Math.log10(mean), ~digits=4);
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let nStd = toPrecisionWithPrecision(std, ~digits=2);
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let nStd = toPrecisionWithPrecision(Js.Math.log10(std), ~digits=2);
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{j|lognormal($(nMean), $(nStd))|j};
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}
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);
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@ -58,7 +58,14 @@ module Value = {
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| TimeLimitedDomainCdfLazy(r) =>
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let timeLimited = r(CdfLibrary.Distribution.fromString(_, 1000));
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let cdf = timeLimited.limitedDomainCdf.distribution;
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<> <Chart height=100 data={cdf |> Types.toJs} /> </>;
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<>
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<Chart height=100 data={cdf |> Types.toJs} />
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<Chart
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height=100
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data={cdf |> CdfLibrary.Distribution.toPdf |> Types.toJs}
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/>
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{FloatCdf.logNormal(50., 20.) |> ReasonReact.string}
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</>;
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| TimeLimitedDomainCdf(r) =>
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let cdf: Types.distribution = r.limitedDomainCdf.distribution;
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<> <Chart height=100 data={cdf |> Types.toJs} /> </>;
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@ -122,8 +122,14 @@ module Model = {
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),
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)
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| CHANCE_OF_EXISTENCE =>
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let yearDiff = MomentRe.diff(dateTime, currentDateTime, `days) /. 365.;
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Prop.Value.Probability((100. -. yearDiff) /. 100.);
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let lazyDistribution = r =>
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TimeLimitedDomainCdf.make(
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~timeVector={zero: currentDateTime, unit: `years},
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~distribution=r(FloatCdf.logNormal(10., 2.)),
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~probabilityAtMaxX=0.7,
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~maxX=`x(200.),
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);
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Prop.Value.TimeLimitedDomainCdfLazy(lazyDistribution);
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};
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};
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};
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@ -3,7 +3,7 @@ module Model = {
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let lazyDistribution = r =>
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TimeLimitedDomainCdf.make(
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~timeVector={zero: currentDateTime, unit: `years},
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~distribution=r("normal(50,30)"),
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~distribution=r(FloatCdf.logNormal(20., 3.)),
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~probabilityAtMaxX=0.7,
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~maxX=`x(200.),
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);
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