diff --git a/packages/website/docs/Api/Danger.md b/packages/website/docs/Api/Danger.md new file mode 100644 index 00000000..69a56705 --- /dev/null +++ b/packages/website/docs/Api/Danger.md @@ -0,0 +1,96 @@ +--- +sidebar_position: 10 +title: Danger +--- + +The Danger library contains newer experimental functions which are less stable than Squiggle as a whole. Beware: their name, behavior, namespace or existence may change at any time. + +### laplace + +```js +Danger.laplace: (number, number) => number +``` + +Calculates the probability implied by [Laplace's rule of succession](https://en.wikipedia.org/wiki/Rule_of_succession) + +```js +trials = 10 +successes = 1 +Danger.laplace(trials, successes) // (successes + 1) / (trials + 2) = 2 / 12 = 0.1666 +``` + +### factorial + +```js +Danger.factorial: (number) => number +``` + +Returns the factorial of a number + +### choose + +```js +Danger.choose: (number, number) => number +``` + +`Danger.choose(n,k)` returns `factorial(n) / (factorial(n - k) *.factorial(k))`, i.e., the number of ways you can choose k items from n choices, without repetition. This function is also known as the [binomial coefficient](https://en.wikipedia.org/wiki/Binomial_coefficient). + +### binomial + +```js +Danger.binomial: (number, number, number) => number +``` + +`Danger.binomial(n, k, p)` returns `choose((n, k)) * pow(p, k) * pow(1 - p, n - k)`, i.e., the probability that an event of probability p will happen exactly k times in n draws. + +### integrateFunctionBetweenWithNumIntegrationPoints + +```js +Danger.integrateFunctionBetweenWithNumIntegrationPoints: (number => number, number, number, number) => number +``` + +`Danger.integrateFunctionBetweenWithNumIntegrationPoints(f, min, max, numIntegrationPoints)` integrates the function `f` between `min` and `max`, and computes `numIntegrationPoints` in between to do so. + +Note that the function `f` has to take in and return numbers. To integrate a function which returns distributios, use: + +```js +auxiliaryF(x) = mean(f(x)) + +Danger.integrateFunctionBetweenWithNumIntegrationPoints(auxiliaryF, min, max, numIntegrationPoints) +``` + +### integrateFunctionBetweenWithEpsilon + +```js +Danger.integrateFunctionBetweenWithEpsilon: (number => number, number, number, number) => number +``` + +`Danger.integrateFunctionBetweenWithEpsilon(f, min, max, epsilon)` integrates the function `f` between `min` and `max`, and uses an interval of `epsilon` between integration points when doing so. This makes its runtime less predictable than `integrateFunctionBetweenWithNumIntegrationPoints`, because runtime will not only depend on `epsilon`, but also on `min` and `max`. + +Same caveats as `integrateFunctionBetweenWithNumIntegrationPoints` apply. + +### optimalAllocationGivenDiminishingMarginalReturnsFunctions2 + +```js +Danger.optimalAllocationGivenDiminishingMarginalReturnsFunctions2: (number => number, number => number, number, number) => number +``` + +`Danger.optimalAllocationGivenDiminishingMarginalReturnsFunctions2(f1, f2, funds, approximateIncrement)` computes the optimal allocation of $`funds` between `f1` and `f2`. For the answer given to be correct, `f1` and `f2` will have to be decreasing, i.e., if `x > y`, then `f_i(x) < f_i(y)` + +Example: + +```js +Danger.optimalAllocationGivenDiminishingMarginalReturnsFunctions2({|x| 20-x}, {|y| 10}, 100, 0.01) +``` + +### optimalAllocationGivenDiminishingMarginalReturnsFunctions3 to optimalAllocationGivenDiminishingMarginalReturnsFunctions7 + +Equivalent to the above, but they take more functional arguments. Their type is given below: + +```js +Danger.optimalAllocationGivenDiminishingMarginalReturnsFunctions3: (number => number, number => number, number => number, number, number) => number +Danger.optimalAllocationGivenDiminishingMarginalReturnsFunctions5: (number => number, number => number, umber => number, number => number, number, number) => number +Danger.optimalAllocationGivenDiminishingMarginalReturnsFunctions5: (number => number, number => number, umber => number, number => number, number => number, number, number) => number +Danger.optimalAllocationGivenDiminishingMarginalReturnsFunctions6: (number => number, number => number, number => number, number => number, number => number, number => number, number, number) => number +Danger.optimalAllocationGivenDiminishingMarginalReturnsFunctions7: (number => number, number => number, number => number, number => number, umber => number, number => number, number => number, number, number) => number +``` \ No newline at end of file