View source: R/distribution-methods.R
tfd_stddev | R Documentation |
Standard deviation is defined as, stddev = E[(X - E[X])**2]**0.5
#' where X is the random variable associated with this distribution, E denotes expectation,
and Var$shape = batch_shape + event_shape
.
tfd_stddev(distribution, ...)
distribution |
The distribution being used. |
... |
Additional parameters passed to Python. |
a Tensor of shape sample_shape(x) + self$batch_shape
with values of type self$dtype
.
Other distribution_methods:
tfd_cdf()
,
tfd_covariance()
,
tfd_cross_entropy()
,
tfd_entropy()
,
tfd_kl_divergence()
,
tfd_log_cdf()
,
tfd_log_prob()
,
tfd_log_survival_function()
,
tfd_mean()
,
tfd_mode()
,
tfd_prob()
,
tfd_quantile()
,
tfd_sample()
,
tfd_survival_function()
,
tfd_variance()
d <- tfd_normal(loc = c(1, 2), scale = c(1, 0.5)) d %>% tfd_stddev()
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