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1. A simple procedure for sampling a di... A simple procedure for sampling a distribution to look like another. A method through binning and another by kde estimation. The binning idea came from this stats exchange question and the kde method came from other studies of mine.

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   library(tidyverse)

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   library(broom)

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   df <- 

2. Little function I created in R for a... Little function I created in R for adding all lagged values up to n of a variable to a df. Can be improved for handling more than one variable.

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   add_lagged <- function(df, var, n = 1) {

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     var <- enquo(var)

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     names <- map(1:n, ~ paste0(quo_name(var), '_lag_' ,.))

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     lagged_cols <- map2(1:n, names, ~ df %>% transmute(!!.y := lag(!!var, n = .x))) %>% 

3. A small little idea on implementing ... A small little idea on implementing bootstrap only using purrr, not dplyr based, after reading a google data science blog

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   ## http://www.unofficialgoogledatascience.com/2015/08/an-introduction-to-poisson-bootstrap26.html

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   n <- 10000000

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   data <- rnorm(n, mean = 4, sd = 2)

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4. quick log odds, odds, probability eq... quick log odds, odds, probability equivalence

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   library(dplyr)

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   tibble(

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   	prob = seq(0, 1, 0.01), 

5. Um simples script que cria 300 variá... Um simples script que cria 300 variáveis normais de 100 pares de média e variância distintas e calcula suas médias e intervalos de confiança por meio do bootstrap e ainda calcula a proporção de vezes que a verdadeira média esta no intervalo

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   library(tidyverse)

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   ### criando 300 váriáveis normais para 20 diferentes 

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   ### pares de média e variância distintos 

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6. This decorator caches a pandas.DataF... This decorator caches a pandas.DataFrame returning function. It saves the pandas.DataFrame in a parquet file in the cache_dir.

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   import pandas as pd

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   from pathlib import Path

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   from functools import wraps

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   def cache_pandas_result(cache_dir, hard_reset: bool):