bssm_prior: Prior objects for bssm models

In bssm: Bayesian Inference of Non-Linear and Non-Gaussian State Space Models

Prior objects for bssm models

Description

These simple objects of class bssm_prior are used to construct a prior distributions for the some of the model objects of bssm package. Currently supported priors are uniform (uniform()), half-normal (halfnormal()), normal (normal()), gamma (gamma), and truncated normal distribution (tnormal()). All parameters are vectorized so for regression coefficient vector beta you can define prior for example as normal(0, 0, c(10, 20)).

Usage

uniform_prior(init, min, max)

uniform(init, min, max)

halfnormal_prior(init, sd)

halfnormal(init, sd)

normal_prior(init, mean, sd)

normal(init, mean, sd)

tnormal_prior(init, mean, sd, min = -Inf, max = Inf)

tnormal(init, mean, sd, min = -Inf, max = Inf)

gamma_prior(init, shape, rate)

gamma(init, shape, rate)

Arguments

init	Initial value for the parameter, used in initializing the model components and as a starting values in MCMC.
min	Lower bound of the uniform and truncated normal prior.
max	Upper bound of the uniform and truncated normal prior.
sd	Positive value defining the standard deviation of the (underlying i.e. non-truncated) Normal distribution.
mean	Mean of the Normal prior.
shape	Positive shape parameter of the Gamma prior.
rate	Positive rate parameter of the Gamma prior.

Details

The longer name versions of the prior functions with _prior ending are identical with shorter versions and they are available only to avoid clash with R's primitive function gamma (other long prior names are just for consistent naming).

Value

object of class bssm_prior or bssm_prior_list in case of multiple priors (i.e. multiple regression coefficients).

Examples

# create uniform prior on [-1, 1] for one parameter with initial value 0.2:
uniform(init = 0.2, min = -1.0, max = 1.0)
# two normal priors at once i.e. for coefficients beta:
normal(init = c(0.1, 2.5), mean = 0.1, sd = c(1.5, 2.8))
# Gamma prior (not run because autotest tests complain)
# gamma(init = 0.1, shape = 2.5, rate = 1.1)
# Same as
gamma_prior(init = 0.1, shape = 2.5, rate = 1.1)
# Half-normal
halfnormal(init = 0.01, sd = 0.1)
# Truncated normal
tnormal(init = 5.2, mean = 5.0, sd = 3.0, min = 0.5, max = 9.5)


# Further examples for diagnostic purposes:
uniform(c(0, 0.2), c(-1.0, 0.001), c(1.0, 1.2))
normal(c(0, 0.2), c(-1.0, 0.001), c(1.0, 1.2))
tnormal(c(2, 2.2), c(-1.0, 0.001), c(1.0, 1.2), c(1.2, 2), 3.3)
halfnormal(c(0, 0.2), c(1.0, 1.2))
# not run because autotest bug 
# gamma(c(0.1, 0.2), c(1.2, 2), c(3.3, 3.3))

# longer versions:
uniform_prior(init = c(0, 0.2), min = c(-1.0, 0.001), max = c(1.0, 1.2))
normal_prior(init = c(0, 0.2), mean = c(-1.0, 0.001), sd = c(1.0, 1.2))
tnormal_prior(init = c(2, 2.2), mean = c(-1.0, 0.001), sd = c(1.0, 1.2), 
  min = c(1.2, 2), max = 3.3)
halfnormal_prior(init = c(0, 0.2), sd = c(1.0, 1.2))
gamma_prior(init = c(0.1, 0.2), shape = c(1.2, 2), rate = c(3.3, 3.3))

bssm documentation built on May 4, 2022, 1:06 a.m.