This distribution is parameterized by probs
, a (batch of) probabilities for
drawing a 1
and total_count
, the number of trials per draw from the
Binomial.
tfd_binomial(total_count, logits = NULL, probs = NULL, validate_args = FALSE, allow_nan_stats = TRUE, name = "Beta")
total_count  Nonnegative floating point tensor with shape broadcastable
to 

logits  Floating point tensor representing the logodds of a
positive event with shape broadcastable to 
probs  Positive floating point tensor with shape broadcastable to

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. 
a distribution instance.
Mathematical Details
The Binomial is a distribution over the number of 1
's in total_count
independent trials, with each trial having the same probability of 1
, i.e.,
probs
.
The probability mass function (pmf) is,
pmf(k; n, p) = p**k (1  p)**(n  k) / Z Z = k! (n  k)! / n!
where:
total_count = n
,
probs = p
,
Z
is the normalizing constant, and,
n!
is the factorial of n
.
For usage examples see e.g. tfd_sample()
, tfd_log_prob()
, tfd_mean()
.
Other distributions: tfd_autoregressive
,
tfd_batch_reshape
,
tfd_bernoulli
, tfd_beta
,
tfd_categorical
, tfd_cauchy
,
tfd_chi2
, tfd_chi
,
tfd_cholesky_lkj
,
tfd_deterministic
,
tfd_dirichlet_multinomial
,
tfd_dirichlet
, tfd_empirical
,
tfd_exponential
,
tfd_gamma_gamma
, tfd_gamma
,
tfd_gaussian_process_regression_model
,
tfd_gaussian_process
,
tfd_geometric
, tfd_gumbel
,
tfd_half_cauchy
,
tfd_half_normal
,
tfd_hidden_markov_model
,
tfd_horseshoe
,
tfd_independent
,
tfd_inverse_gamma
,
tfd_inverse_gaussian
,
tfd_joint_distribution_named
,
tfd_joint_distribution_sequential
,
tfd_kumaraswamy
, tfd_laplace
,
tfd_linear_gaussian_state_space_model
,
tfd_lkj
, tfd_log_normal
,
tfd_logistic
,
tfd_mixture_same_family
,
tfd_mixture
, tfd_multinomial
,
tfd_multivariate_normal_diag_plus_low_rank
,
tfd_multivariate_normal_diag
,
tfd_multivariate_normal_full_covariance
,
tfd_multivariate_normal_linear_operator
,
tfd_multivariate_normal_tri_l
,
tfd_multivariate_student_t_linear_operator
,
tfd_negative_binomial
,
tfd_normal
,
tfd_one_hot_categorical
,
tfd_pareto
, tfd_pixel_cnn
,
tfd_poisson_log_normal_quadrature_compound
,
tfd_poisson
,
tfd_probit_bernoulli
,
tfd_quantized
,
tfd_relaxed_bernoulli
,
tfd_relaxed_one_hot_categorical
,
tfd_sample_distribution
,
tfd_sinh_arcsinh
,
tfd_student_t_process
,
tfd_student_t
,
tfd_transformed_distribution
,
tfd_triangular
,
tfd_truncated_normal
,
tfd_uniform
,
tfd_variational_gaussian_process
,
tfd_vector_diffeomixture
,
tfd_vector_exponential_diag
,
tfd_vector_exponential_linear_operator
,
tfd_vector_laplace_diag
,
tfd_vector_laplace_linear_operator
,
tfd_vector_sinh_arcsinh_diag
,
tfd_von_mises_fisher
,
tfd_von_mises
,
tfd_wishart_linear_operator
,
tfd_wishart_tri_l
,
tfd_wishart
, tfd_zipf