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rdataframepoisson
Renzo Giudice
Renzo Giudice

Reputation: 35

How to add simulated values from a poisson distribution for each row and add them into the dataframe

I am trying to expand a dataframe by including, for each row, 500 simulated values from a Poisson distribution whose parameter Theta (count_mean) is already stored in the dataframe. In the example below I am only providing a dataframe example, since my real data is composed by more than 50,000 rows (i.e. ids).

example.data <- data.frame(id=c("4008", "4118", "5330"), 
                       count_mean=c(2, 25, 11)
                       )

So for each row, I know I have to generate the simulated values by:

rpois(500, example.data$count_mean)

How can I introduce these values into the same dataframe, in which each new column presents one simulated value for each row?

Upvotes: 0

Views: 307

Answers (2)

Martin Gal
Martin Gal

Reputation: 16998

Another option using dplyr and tidyr:

example.data %>% 
  rowwise() %>%
  mutate(poisson = list(rpois(500, count_mean))) %>%
  unnest(poisson) %>%
  group_by(id) %>%
  mutate(count=row_number()) %>%
  pivot_wider(names_from="count", names_prefix="sim_", values_from="poisson")

Upvotes: 0

Cettt
Cettt

Reputation: 11981

You can use sapply to simulate the numbers and then use cbind to bind your data together:

simdata <- t(sapply(example.data$count_mean, function(x) rpois(500, x)))

colnames(simdata) <- paste0("sim_", 1:500)

cbind(example.data, simdata)

However, I would encourage you to work with a different data format: maybe a long table would be more appropriate in this situation than the current wide table.

Upvotes: 1

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