Nothing
## ---- include = FALSE---------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----frame--------------------------------------------------------------------
library(sps)
set.seed(123654)
frame <- data.frame(
revenue = round(rlnorm(1e3) * 1000),
region = sample(1:3, 1e3, prob = c(0.2, 0.3, 0.5), replace = TRUE)
)
head(frame)
## ----outcome------------------------------------------------------------------
sales <- round(frame$revenue * runif(1e3, 0.5, 2))
## ----allocation---------------------------------------------------------------
allocation <- with(frame, prop_allocation(revenue, 100, region))
allocation
## ----sample-------------------------------------------------------------------
sample <- with(frame, sps(revenue, allocation, region))
survey <- cbind(frame[sample, ], sales = sales[sample])
head(survey)
## ----weights------------------------------------------------------------------
survey$weight <- weights(sample)
head(survey)
## ----estimate-----------------------------------------------------------------
ht <- with(survey, sum(sales * weight))
ht
## ----bias---------------------------------------------------------------------
ht / sum(sales) - 1
## ----variance-----------------------------------------------------------------
repweights <- sps_repweights(weights(sample), tau = 2)
var <- attr(repweights, "tau")^2 *
mean((colSums(survey$sales * repweights) - ht)^2)
sqrt(var) / ht
## ----variance2----------------------------------------------------------------
sps_var <- function(y, w) {
y <- y[w > 1]
w <- w[w > 1]
n <- length(y)
Y <- sum(y * w)
n / (n - 1) * sum((1 - 1 / w) * (w * y - Y / n)^2)
}
var <- with(
survey,
mapply(sps_var, split(sales, region), split(weight, region))
)
sqrt(sum(var)) / ht
## ----prns---------------------------------------------------------------------
frame$prn <- runif(1000)
head(frame)
## ----prn samples--------------------------------------------------------------
pareto <- order_sampling(\(x) x / (1 - x))
sample <- with(frame, sps(revenue, allocation, region, prn))
parsample <- with(frame, pareto(revenue, allocation, region, (prn - 0.5) %% 1))
length(intersect(sample, parsample)) / 100
## ----prn simualtion-----------------------------------------------------------
replicate(1000, {
s <- with(frame, pareto(revenue, allocation, region))
length(intersect(sample, s)) / 100
}) |>
summary()
## ----top up-------------------------------------------------------------------
sample <- with(frame, sps(revenue, allocation, region, prn))
sample_tu <- with(frame, sps(revenue, allocation + c(10, 0, 0), region, prn))
all(sample %in% sample_tu)
## ----critical-----------------------------------------------------------------
becomes_ta <- function(x, alpha = 1e-3) {
ord <- rev(order(x, decreasing = TRUE))
x <- x[ord]
res <- ceiling(cumsum(x) / x * (1 - alpha)) + length(x) - seq_along(x)
res[order(ord)]
}
Map(\(x) head(becomes_ta(x)), split(frame$revenue, frame$region))
## ----no_tu--------------------------------------------------------------------
set.seed(13026)
x <- rlnorm(10)
u <- runif(10)
becomes_ta(x)
sample <- sps(x, 4, prn = u)
sample %in% sps(x, 5, prn = u)
## ----yes_tu-------------------------------------------------------------------
sample %in% sps(x, 6, prn = u)
## ----ht bias------------------------------------------------------------------
sampling_distribution <- replicate(1000, {
sample <- with(frame, sps(revenue, allocation, region))
sum(sales[sample] * weights(sample))
})
summary(sampling_distribution / sum(sales) - 1)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.