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h2o.var

Variance of a column or covariance of columns.


Description

Compute the variance or covariance matrix of one or two H2OFrames.

Usage

h2o.var(x, y = NULL, na.rm = FALSE, use)

var(x, y = NULL, na.rm = FALSE, use)

Arguments

x

An H2OFrame object.

y

NULL (default) or an H2OFrame. The default is equivalent to y = x.

na.rm

logical. Should missing values be removed?

use

An optional character string indicating how to handle missing values. This must be one of the following: "everything" - outputs NaNs whenever one of its contributing observations is missing "all.obs" - presence of missing observations will throw an error "complete.obs" - discards missing values along with all observations in their rows so that only complete observations are used

See Also

cor for the base R implementation, var(). h2o.sd for standard deviation.

Examples

## Not run: 
library(h2o)
h2o.init()

prostate_path <- system.file("extdata", "prostate.csv", package = "h2o")
prostate <- h2o.uploadFile(path = prostate_path)
var(prostate$AGE)

## End(Not run)

h2o

R Interface for the 'H2O' Scalable Machine Learning Platform

v3.32.1.2
Apache License (== 2.0)
Authors
Erin LeDell [aut, cre], Navdeep Gill [aut], Spencer Aiello [aut], Anqi Fu [aut], Arno Candel [aut], Cliff Click [aut], Tom Kraljevic [aut], Tomas Nykodym [aut], Patrick Aboyoun [aut], Michal Kurka [aut], Michal Malohlava [aut], Ludi Rehak [ctb], Eric Eckstrand [ctb], Brandon Hill [ctb], Sebastian Vidrio [ctb], Surekha Jadhawani [ctb], Amy Wang [ctb], Raymond Peck [ctb], Wendy Wong [ctb], Jan Gorecki [ctb], Matt Dowle [ctb], Yuan Tang [ctb], Lauren DiPerna [ctb], Tomas Fryda [ctb], H2O.ai [cph, fnd]
Initial release
2021-04-29

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