Generate resamples, permutations, or simulations
Generation creates a null distribution from specify() and (if needed)
hypothesize() inputs.
Learn more in vignette("infer").
generate(x, reps = 1, type = NULL, ...)
x |
A data frame that can be coerced into a tibble. |
reps |
The number of resamples to generate. |
type |
Currently either |
... |
Currently ignored. |
A tibble containing reps generated datasets, indicated by the
replicate column.
The type argument determines the method used to create the null
distribution.
bootstrap: A bootstrap sample will be drawn for each replicate,
where a sample of size equal to the input sample size is drawn (with
replacement) from the input sample data.
permute: For each replicate, each input value will be randomly
reassigned (without replacement) to a new output value in the sample.
simulate: A value will be sampled from a theoretical distribution
with parameters specified in hypothesize() for each replicate. (This
option is currently only applicable for testing point estimates.)
# Generate a null distribution by taking 200 bootstrap samples
gss %>%
specify(response = hours) %>%
hypothesize(null = "point", mu = 40) %>%
generate(reps = 200, type = "bootstrap")
# Generate a null distribution for the independence of
# two variables by permuting their values 1000 times
gss %>%
specify(partyid ~ age) %>%
hypothesize(null = "independence") %>%
generate(reps = 200, type = "permute")
# More in-depth explanation of how to use the infer package
## Not run:
vignette("infer")
## End(Not run)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.