Last observation carried forward (LOCF) imputation

Replaces each NA in a vector with the most recent preceding non-NA value (last observation carried forward, LOCF). If the first element is NA, it is replaced with the first non-NA value found anywhere in the vector. To apply LOCF to every column of a data frame use df[] <- lapply(df, replace_na_with_previous).

Usage

replace_na_with_previous(vector)

Arguments

vector

A vector of any type that may contain NA values.

Value

A vector of the same length and type as vector with NA values replaced by the preceding non-NA element. Returns the original vector unchanged if it contains no NA values.

Examples

set.seed(12345)
df1 <- generate_missing(rnorm(10), missing = 5)
df2 <- generate_missing(rnorm(10), missing = 5)
df3 <- generate_missing(rnorm(10), missing = 5)
df4 <- generate_missing(rnorm(10), missing = 5)
df5 <- generate_missing(rnorm(10), missing = 5)
df <- data.frame(df1, df2, df3, df4, df5)
row.names(df) <- paste0("A", row.names(df))
replace_na_with_previous(df1)
#>  [1]  0.7095  0.7095 -0.1093 -0.4535  0.6059  0.6059  0.6059  0.6059 -0.2842 -0.2842
df[] <- lapply(df, replace_na_with_previous)