feat: add C implementation for stats/base/dists/erlang/cdf

[Lokeshranjan8]

Resolves #3568 .

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• adds C implementation for stats/base/dists/erlang/cdf along with relevant docs, tests, examples and benchmarks

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Coverage Report

Package	Statements	Branches	Functions	Lines
stats/base/dists/erlang/cdf	$\color{green}290/290$ $\color{green}+100.00%$	$\color{green}11/11$ $\color{green}+100.00%$	$\color{green}3/3$ $\color{green}+100.00%$	$\color{green}290/290$ $\color{green}+100.00%$

The above coverage report was generated for the changes in this PR.

[Neerajpathak07]

@Lokeshranjan8 Have left out an inital round of comments. Mainly you'll have to check your implementation and rectify which dtype k uses and which corresponding macro will be required for it.
To get a good idea of the current code convention for these pacakges take a look at:- https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/base/dists/wald/pdf

[Neerajpathak07]

could you streamline this test cases to adhere to the latest code convention which we follow for statistical distribution packages.
you can refer to:-

stdlib/lib/node_modules/@stdlib/stats/base/dists/wald/pdf/test/test.pdf.js

Line 197 in d9a5e08

tape( 'the function evaluates the pdf for `x` given parameters `mu` and `lambda`', function test( t ) {

here you mainly have to update the upstream fixtures for the package to house them inside a single data.json file. After which it can be sourced to test various edge cases as per done in the ref above.

Another nitpick would be to use isAlmostSameValue.