Code
mixture(bernoulli(0.5), normal(0, 1), weights = weights)
Condition
Error in `initialize()`:
! Cannot construct a mixture distribution from a combination of discrete and continuous distributions
Code
mixture(multivariate_normal(zeros(1, 3), diag(3)), normal(0, 1, dim = c(1, 3)),
weights = weights)
Condition
Error in `initialize()`:
! Cannot construct a mixture from a combination of multivariate and univariate distributions
Code
mixture(normal(0, 1, truncation = c(0, Inf)), normal(0, 1), weights = weights)
Condition
Error in `initialize()`:
! Component distributions must have the same support
However the component distributions have different support:
"0 to Inf vs. -Inf to Inf"
Code
mixture(lognormal(0, 1), normal(0, 1), weights = weights)
Condition
Error in `initialize()`:
! Component distributions must have the same support
However the component distributions have different support:
"0 to Inf vs. -Inf to Inf"
Code
mixture(normal(0, 1), normal(0, 2), weights = weights)
Condition
Error in `initialize()`:
! The first dimension of weights must be the number of distributions in the mixture (2)
However it was 1
Code
mixture(normal(0, 2), weights = weights)
Condition
Error in `initialize()`:
! `mixture()` must be passed at least 2 distributions
The number of distributions passed was: 1
Code
mixture(weights = weights)
Condition
Error in `initialize()`:
! `mixture()` must be passed at least 2 distributions
The number of distributions passed was: 0
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