tfd_vector_deterministic: Vector Deterministic Distribution

In tfprobability: Interface to 'TensorFlow Probability'

Vector Deterministic Distribution

Description

The VectorDeterministic distribution is parameterized by a batch point loc in R^k. The distribution is supported at this point only, and corresponds to a random variable that is constant, equal to loc.

Usage

tfd_vector_deterministic(
  loc,
  atol = NULL,
  rtol = NULL,
  validate_args = FALSE,
  allow_nan_stats = TRUE,
  name = "VectorDeterministic"
)

Arguments

loc	Numeric Tensor of shape [B1, ..., Bb, k], with b >= 0, k >= 0 The point (or batch of points) on which this distribution is supported.
atol	Non-negative Tensor of same dtype as loc and broadcastable shape. The absolute tolerance for comparing closeness to loc. Default is 0.
rtol	Non-negative Tensor of same dtype as loc and broadcastable shape. The relative tolerance for comparing closeness to loc. Default is 0.
validate_args	Logical, default FALSE. When TRUE distribution parameters are checked for validity despite possibly degrading runtime performance. When FALSE invalid inputs may silently render incorrect outputs. Default value: FALSE.
allow_nan_stats	Logical, default TRUE. When TRUE, statistics (e.g., mean, mode, variance) use the value NaN to indicate the result is undefined. When FALSE, an exception is raised if one or more of the statistic's batch members are undefined.
name	name prefixed to Ops created by this class.

Details

See Degenerate rv.

Value

a distribution instance.

See Also

For usage examples see e.g. tfd_sample(), tfd_log_prob(), tfd_mean().

tfprobability documentation built on Sept. 1, 2022, 5:07 p.m.