set_sampler: Update the sampler used for a specific variable
In JasperHG90/blm: Bayesian linear model
Description
Usage
Arguments
Value
Examples
Description
The use can set the sampler to either (1) 'Gibbs' (default for all coefficients) or (2) 'MH' (metropolis-hastings algorithm, only for coefficients).
Usage
1
set_sampler(x, ...)
Arguments
x
a blm object
par
name of the coefficient, given as b0 (intercept) or b1, ... for coefficients.
type
name of the sampler to use. Either 'Gibbs' or 'MH'. Defaults to 'Gibbs'.
lambda
tuning parameter for the variance of the proposal distribution in metropolis-hastings
Value
updated blm object
Examples
1
bfit <- set_sampler(bfit, "b0", type="MH")
JasperHG90/blm documentation built on Sept. 4, 2019, 11:16 a.m.
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Description Usage Arguments Value Examples
Description
The use can set the sampler to either (1) 'Gibbs' (default for all coefficients) or (2) 'MH' (metropolis-hastings algorithm, only for coefficients).
Usage
1 | set_sampler(x, ...)
|
Arguments
x |
a blm object |
par |
name of the coefficient, given as b0 (intercept) or b1, ... for coefficients. |
type |
name of the sampler to use. Either 'Gibbs' or 'MH'. Defaults to 'Gibbs'. |
lambda |
tuning parameter for the variance of the proposal distribution in metropolis-hastings |
Value
updated blm object
Examples
1 | bfit <- set_sampler(bfit, "b0", type="MH")
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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