Type SinhArcsinh
Namespace tensorflow.contrib.distributions.bijectors
Parent Bijector
Interfaces ISinhArcsinh
Compute `Y = g(X) = Sinh( (Arcsinh(X) + skewness) * tailweight )`. For `skewness in (-inf, inf)` and `tailweight in (0, inf)`, this
transformation is a
diffeomorphism of the real line `(-inf, inf)`. The inverse transform is
`X = g^{-1}(Y) = Sinh( ArcSinh(Y) / tailweight - skewness )`. The `SinhArcsinh` transformation of the Normal is described in
[Sinh-arcsinh distributions](https://www.jstor.org/stable/27798865)
This Bijector allows a similar transformation of any distribution supported on
`(-inf, inf)`. #### Meaning of the parameters * If `skewness = 0` and `tailweight = 1`, this transform is the identity.
* Positive (negative) `skewness` leads to positive (negative) skew.
* positive skew means, for unimodal `X` centered at zero, the mode of `Y` is
"tilted" to the right.
* positive skew means positive values of `Y` become more likely, and
negative values become less likely.
* Larger (smaller) `tailweight` leads to fatter (thinner) tails.
* Fatter tails mean larger values of `|Y|` become more likely.
* If `X` is a unit Normal, `tailweight < 1` leads to a distribution that is
"flat" around `Y = 0`, and a very steep drop-off in the tails.
* If `X` is a unit Normal, `tailweight > 1` leads to a distribution more
peaked at the mode with heavier tails. To see the argument about the tails, note that for `|X| >> 1` and
`|X| >> (|skewness| * tailweight)**tailweight`, we have
`Y approx 0.5 X**tailweight e**(sign(X) skewness * tailweight)`.
Properties
- dtype
- dtype_dyn
- forward_min_event_ndims
- forward_min_event_ndims_dyn
- graph_parents
- graph_parents_dyn
- inverse_min_event_ndims
- inverse_min_event_ndims_dyn
- is_constant_jacobian
- is_constant_jacobian_dyn
- name
- name_dyn
- PythonObject
- skewness
- skewness_dyn
- tailweight
- tailweight_dyn
- validate_args
- validate_args_dyn
Public properties
object dtype get;
object dtype_dyn get;
object forward_min_event_ndims get;
object forward_min_event_ndims_dyn get;
IList<object> graph_parents get;
object graph_parents_dyn get;
object inverse_min_event_ndims get;
object inverse_min_event_ndims_dyn get;
bool is_constant_jacobian get;
object is_constant_jacobian_dyn get;
object name get;
object name_dyn get;
object PythonObject get;
Tensor skewness get;
The `skewness` in: `Y = Sinh((Arcsinh(X) + skewness) * tailweight)`.
object skewness_dyn get;
The `skewness` in: `Y = Sinh((Arcsinh(X) + skewness) * tailweight)`.
object tailweight get;
The `tailweight` in: `Y = Sinh((Arcsinh(X) + skewness) * tailweight)`.
object tailweight_dyn get;
The `tailweight` in: `Y = Sinh((Arcsinh(X) + skewness) * tailweight)`.