Description Details See Also Examples

A `Prior`

object represents a prior distribution on the single model
parameter of a `DataDistribution`

class
object.
Together a prior and data-distribution specify the class of the joint
distribution of the test statisic, X, and its parameter, theta.
Currently, adoptr only allows simple models with a single parameter.
Implementations for PointMassPrior and ContinuousPrior are available.

For an example on working with priors, see here.

For the available methods, see `bounds`

,
`expectation`

, `condition`

, `predictive_pdf`

,
`predictive_cdf`

, `posterior`

1 2 3 4 5 6 | ```
disc_prior <- PointMassPrior(c(0.1, 0.25), c(0.4, 0.6))
cont_prior <- ContinuousPrior(
pdf = function(x) dnorm(x, mean = 0.3, sd = 0.2),
support = c(-2, 3)
)
``` |

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