Create a `markovChain.js` module (#271)

Summary:
For now, this module has just two types: `Distribution` and
`SparseMarkovChain`. We’ll gradually pull code from `basicPagerank` into
this module, adding unit tests along the way.

Test Plan:
None required.

wchargin-branch: markov-chain-module

src/core/attribution/markovChain.js

@@ -0,0 +1,28 @@
+// @flow
+
+/**
+ * A distribution over the integers `0` through `n - 1`, where `n` is
+ * the length of the array. The value at index `i` is the probability of
+ * `i` in the distribution. The values should sum to 1.
+ */
+export type Distribution = Float64Array;
+
+/**
+ * A representation of a sparse transition matrix that is convenient for
+ * computations on Markov chains.
+ *
+ * A Markov chain has nodes indexed from `0` to `n - 1`, where `n` is
+ * the length of the chain. The elements of the chain represent the
+ * incoming edges to each node. Specifically, for each node `v`, the
+ * in-degree of `v` equals the length of both `chain[v].neighbor` and
+ * `chain[v].weight`. For each `i` from `0` to the degree of `v`
+ * (exclusive), there is an edge to `v` from `chain[v].neighbor[i]` with
+ * weight `chain[v].weight[i]`.
+ *
+ * In other words, `chain[v]` is a sparse-vector representation of
+ * column `v` of the transition matrix of the Markov chain.
+ */
+export type SparseMarkovChain = $ReadOnlyArray<{|
+  +neighbor: Uint32Array,
+  +weight: Float64Array,
+|}>;