benilton

## Este exemplo provê um código em R que outros usuários podem reproduzir
## para facilitar a solução de problemas observados.
##
## Na R-br em: http://r-br.2285057.n4.nabble.com/R-br-Produzindo-um-Codigo-Minimo-Reproduzivel-CMR-td3674188.html

#################################################################
## PASSO 1: Carregue os pacotes necessários no início do código
#################################################################
library(splines)

benilton

## Por Benilton Carvalho
##
## Determinando os parâmetros da Normal
media <- 170
stder <- 8
 
## Criando o grid no qual deseja-se visualizar a densidade
x <- seq(media-3*stder, media+3*stder, .01)
 
## Determinando a densidade em cada ponto do grid

benilton

## Installing the oligo package
## Requires biocLite()
source("http://www.bioconductor.org/biocLite.R")
biocLite("oligo")

benilton

## funcao initial
equantileByCounts <- function(x, counts, qs){
    tot <- sum(counts)
    i <- order(x)
    x <- x[i]
    counts <- counts[i]
    partial <- cumsum(counts)
    qsObs <- qs*tot
    start <- floor(qsObs)
    end <- ceiling(qsObs)

benilton

## Conjunto de dados
x = structure(list(pop = c(23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 
23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 
23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 
23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L, 23L), ind = c(12L, 
12L, 14L, 14L, 18L, 18L, 20L, 20L, 21L, 21L, 22L, 22L, 24L, 24L, 
25L, 25L, 26L, 26L, 27L, 27L, 28L, 28L, 29L, 29L, 31L, 31L, 32L, 
32L, 33L, 33L, 34L, 34L, 36L, 36L, 42L, 42L, 49L, 49L, 51L, 52L, 
52L, 58L, 58L, 59L, 59L), morph = c("long", "long", "long", "long", 
"long", "long", "long", "long", "long", "long", "semi-M_AL", 

benilton

volta.cokri2 <- function(mat.cokri, num.simu, retorna.tudo=FALSE, int.conf=0.95){
    ## Author: Wagner Bonat / Ana Beatriz Martins / Paulo Justiniano
    ## Modified for parallel and better use of RAM by: Benilton Carvalho
    require(parallel)
    nlinhas <- dim(mat.cokri[[1]])[1]
    f <- function(i){
        g <- mvrnorm(n=1, mat.cokri[[1]], mat.cokri[[2]])
        seq1 <- seq(1, nlinhas, by=2)
        gerado <- data.frame(g[seq1], g[seq1+1L])

benilton

library(pdInfoBuilder)
seed <- new("AffySTPDInfoPkgSeed",
            version="3.6.0",
            license="Artistic-2.0",
            pgfFile=dir(patt=".pgf$"),
            clfFile=dir(patt=".clf$"),
            probeFile=dir(patt="probeset.csv$"),
            transFile=dir(patt="transcript.csv$"),
            coreMps=dir(patt="core.mps$"),
            fullMps=dir(patt="full.mps$"),

benilton

## Gerando dados
set.seed(1)
y1 = rnorm(20, 2.5, 1.25)
y2 = rnorm(20, 5, 1.25)
Y = c(y1, y2)


data(faithful)
plot(faithful$waiting, faithful$eruptions)

benilton

## Gerando dados
set.seed(1)
y1 = rnorm(20, 2.5, 1.25)
y2 = rnorm(20, 5, 1.25)
Y = c(y1, y2)


##
data(faithful)
plot(faithful$waiting, faithful$eruptions)

benilton

data(cars)
fit = lm(dist ~ speed, data=cars)
summary(fit)

system.time({
  nBoot = 10000
  coefs = rep(NA, nBoot)
  for (j in 1:nBoot){
    i = sample(nrow(cars), replace = TRUE)
    fitBoot = lm(dist ~ speed, data=cars[i,])