pachamaltese - 1 year ago 95
R Question

# plyr + simpleboot: NA in probability vector

I am using

`simpleboot`
package (https://cran.r-project.org/web/packages/simpleboot/index.html) to obtain confidence intervals.

This is my function:

``````lb_weighted_median_dplyr <- function(x,v) {
set.seed(1234)
b <- one.boot(x, weights = v, FUN = function(x,w) matrixStats::weightedMedian(x, w = v, na.rm = TRUE), R = 100, student = FALSE)
round(perc(b, 0.025), 0)
}
``````

What the function does is to calculate the lower bound of the confidence interval when I run

``````ddply(wage_by_gender_2015, .(sex,region), summarise, FUN = lb_weighted_median_dplyr(wage, exp_region))
``````

Where
`wage`
is a numeric column and
`exp_region`
is another numeric column that contains weights.

I don't have data for some regions, therefore the function fails with some regions and returns

``````Error in eval(substitute(expr), envir, enclos) : NA in probability vector
``````

How can I bypass that error and obtain NA as the lower bound for a region without data?

A
`dplyr`
equivalent approach that also returns
`NA in probability vector`
is

``````grouped <- group_by(wage_by_gender_2015, sex, region)
dplyr::summarise(grouped, FUN = lb_weighted_median_dplyr(wage, exp_region))
``````

Relevant sample of the data here: http://users.dcc.uchile.cl/~mvargas/casen/wage_by_gender_2015.RData

``````wage_by_gender_2015 <- data.frame(sex    = rep(c("male", "female"),100),
region = rep(c("north", "south", "east",
"west"), 50),
exp_region = abs(rnorm(100)),
wage       = abs(rnorm(100))
)

wage_by_gender_2015\$exp_region[10] <- NA
ddply(wage_by_gender_2015, .(sex,region), summarise, FUN = lb_weighted_median_dplyr(wage, exp_region))
``````
`````` Error in sample.int(length(x), replace = TRUE, ...) :    NA in probability vector
``````
``````# impute
wage_by_gender_2015\$exp_region <- RRF::na.roughfix(wage_by_gender_2015\$exp_region)

ddply(wage_by_gender_2015, .(sex,region), summarise, FUN = lb_weighted_median_dplyr(wage, exp_region))
``````
``````    sex region FUN
1 female  south   0
2 female   west   0
3   male   east   1
4   male  north   0
``````

As mentioned in the comment I would've used your sample data but it was missing `sex`.

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