formula

Classes

Functions

bf(formula, **formula_args)

Set up a model formula for brms package.

Allows defining (potentially non-linear) additive multilevel models for all parameters of the assumed response distribution.

Parameters:

Name	Type	Description	Default
formula	str	brms formula specification, e.g., "y ~ x + (1|group)"	required
**formula_args	dict	Additional brms::brmsformula() arguments: decomp : str Decomposition method (e.g., "QR" for QR decomposition) center : bool Whether to center predictors (default True) sparse : bool Use sparse matrix representation nl : bool Whether formula is non-linear loop : bool Use loop-based Stan code	{}

Returns:

Type	Description
FormulaResult	Object with .r (R brmsformula object) and .dict (Python dict) attributes

See Also

brms::brmsformula : R documentation https://paulbuerkner.com/brms/reference/brmsformula.html fit : Fit model using formula

Examples:

Basic formula:

    from brmspy import brms
    f = brms.bf("y ~ x1 + x2 + (1|group)")

With QR decomposition for numerical stability:

f = brms.bf(
    "reaction ~ days + (days|subject)",
    decomp="QR"
)

Multivariate formula:

    f = brms.bf(
        "mvbind(y1, y2) ~ x1 + x2",
        center=True
    )

lf(*formulas, flist=None, dpar=None, resp=None, center=None, cmc=None, sparse=None, decomp=None)

Specify linear formulas for distributional / non-linear parameters.

Parameters:

Name	Type	Description	Default
*formulas	str or FormulaResult	One or more formulas (e.g. "sigma ~ x", "nu ~ z").	()
flist	list	Additional formulas passed as a list.	None
dpar	str	Name of the distributional parameter (e.g. "sigma").	None
resp	str	Response name in multivariate models.	None
center	optional	Passed through to brms::lf().	None
cmc	optional	Passed through to brms::lf().	None
sparse	optional	Passed through to brms::lf().	None
decomp	optional	Passed through to brms::lf().	None

Returns:

Type	Description
FormulaResult	Object that can be added to a bf() formula via +.

Examples:

>>> f = bf("y ~ 1") + lf("sigma ~ x", dpar="sigma")

nlf(formula, *extra, flist=None, dpar=None, resp=None, loop=None)

Specify non-linear formulas for distributional parameters.

Parameters:

Name	Type	Description	Default
formula	str	Non-linear formula, e.g. "sigma ~ a * exp(b * x)".	required
*extra	str or FormulaResult	Additional named parameters or formulas (rarely needed here; typically you use lf() for those).	()
flist	list	Additional formulas passed as a list.	None
dpar	str	Name of the distributional parameter.	None
resp	str	Response name in multivariate models.	None
loop	bool	Whether to compute inside a loop (brms::nlf(loop=...)).	None

Returns:

Type	Description
FormulaResult	Object that can be added to a bf() formula via +.

Examples:

>>> f = bf("y ~ 1") + nlf("sigma ~ a * exp(b * x)")

acformula(autocor, resp=None)

Specify autocorrelation terms to add to a model.

Parameters:

Name	Type	Description	Default
autocor	str	One-sided formula with autocorrelation terms, e.g. "~ arma(p = 1, q = 1)".	required
resp	str	Response name in multivariate models.	None

Returns:

Type	Description
FormulaResult	Object that can be added to a bf() formula via +.

Examples:

>>> f = bf("y ~ x") + acformula("~ arma(p = 1, q = 1)")

set_rescor(rescor=True)

Control residual correlations in multivariate models.

Parameters:

Name	Type	Description	Default
rescor	bool	Whether to model residual correlations.	True

Returns:

Type	Description
FormulaResult	Object that can be added to a multivariate formula via +.

Examples:

>>> f = bf("y1 ~ x") + bf("y2 ~ z") + set_rescor(True)

set_mecor(mecor=True)

Control correlations between latent me-terms.

Parameters:

Name	Type	Description	Default
mecor	bool	Whether to model correlations between me() latent variables.	True

Returns:

Type	Description
FormulaResult	Object that can be added to a formula via +.

Examples:

>>> f = bf("y ~ me(x, sdx)") + set_mecor(True)

set_nl(dpar=None, resp=None)

Mark a formula as non-linear (or parts of it).

Parameters:

Name	Type	Description	Default
dpar	str	Distributional parameter name (if only part of the model is non-linear).	None
resp	str	Response name in multivariate models.	None

Returns:

Type	Description
FormulaResult	Object that can be added to a formula via +.

Examples:

>>> f = bf("y ~ a * inv_logit(x * b)") + lf("a + b ~ z") + set_nl()