twolodzko

# code accompanying answer: https://stats.stackexchange.com/a/471245/35989

n <- 22
x <- 13

lik <- function(p) dbinom(x, n, p) * 20
prior <- function(p) dbeta(p, alpha, beta)
post <- function(p) dbeta(p, alpha+x, beta+(n-x))

op <- par(mfrow=c(1,3), mar=c(3,1,1,1), cex=0.9)

twolodzko

twolodzko

twolodzko

twolodzko

#!/bin/bash
set -e

git fetch

BRANCH=$(git rev-parse --abbrev-ref HEAD)
NEWBRANCH="$BRANCH-pr"

if [[ -n $(git rev-parse --verify $NEWBRANCH) ]]; then
    read -p "'$NEWBRANCH' exists, do you want to overwrite it? (y/[n])? " CONTINUE

twolodzko

import numpy as np
import scipy.stats as sp

C = np.array([
    [3, 2, 3],
    [2, 4, 2],
    [3, 2, 3]
])

n = 100_000

twolodzko

Conda

# new env:
conda create --name myenv python=3.7 ipykernel numpy pandas

# remove:
conda remove --name myenv --all

# export:

twolodzko

"""
This is a pure python implementation of t-digest algorithm 1. Parts of the code are borrowed
from https://github.com/CamDavidsonPilon/tdigest

Code is released under The MIT License (MIT).
"""

import math
from typing import List, Tuple, Union, Optional

twolodzko

twolodzko

import numpy as np
import matplotlib.pyplot as plt

class ECDF:
    def __init__(self, arr: np.ndarray, max_points: Optional[int] = None) -> None:
        self.arr = np.sort(arr)
        n = len(self.arr)
        if max_points and n > max_points:
            self.arr = self.arr[:: (n // max_points)]