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Statistics for numeric summaries

Source: R/stats.r
stats.Rd

Functions for computing summary statistics for use in cb_summarize_numeric().

  • skew() and kurtosis() return adjusted skewness and kurtosis. (Unadjusted estimates can be obtained by setting adjusted = FALSE.)

  • spread() returns the difference between a vector's minimum and maximum values.

  • min_if_any() and max_if_any() return minima and maxima with alternate behavior if all values are missing. (Re-exported from the lighthouse package. See lighthouse::min_if_any for more details.)

  • se_mean() returns the standard error of the mean. (Re-exported from the lighthouse package. See lighthouse::se_mean for more details.)

Usage

skew(x, adjusted = TRUE, na.rm = FALSE)

kurtosis(x, adjusted = TRUE, excess = TRUE, na.rm = FALSE)

spread(x, na.rm = FALSE)

min_if_any(..., na.rm = TRUE)

max_if_any(..., na.rm = TRUE)

se_mean(x, na.rm = FALSE)

Arguments

x

A numeric vector.

adjusted

If TRUE, returns adjusted skewness (G1) or kurtosis (G2) by applying a small-sample correction. If FALSE, returns the unadjusted skewness (g1) or kurtosis (g2). (Note that TRUE corresponds to behavior of software such as SPSS, SAS, and Excel.)

na.rm

Should missing values be removed? (Note that cb_summarize_numeric() automatically sets na.rm to TRUE for all functions).

excess

If TRUE, returns excess kurtosis by (total kurtosis - 3).

...

A numeric vector or vectors.