model

Module containing all the generic model functions

Functions

decode_term(term, model, factors)

Decodes the encoded terms (the encoded categorical variables).

encode_model(model, effect_types)

Encodes the model according to the effect types.

encode_names(col_names, effect_types)

Encodes the column names according to the categorical expansion of the factors.

identityY2X(Y)

The identity function.

mixtureY2X(factors, mixture_effects[, ...])

Creates a Scheffe model Y2X with potential process effects and potential cross-terms between the mixture effects and process effects.

mixture_scheffe_model(mixture_effects[, ...])

Creates a Scheffe model with potential process effects and potential cross-terms between the mixture effects and process effects.

model2Y2X(model, factors)

Creates a Y2X function from a model.

model2encnames(model, effect_types[, col_names])

Retrieves the names of the encoded parameters.

model2names(model[, col_names])

Converts the model to parameter names.

order_dependencies(model, factors)

Create a dependency matrix from a model where interactions and higher order effects depend on their components and lower order effects.

partial_rsm(nquad, ntfi, nlin)

Creates a partial response surface model from a number of quadratic, two-factor interactions (tfi) and linear terms.

partial_rsm_names(effects)

Creates a partial response surface model partial_rsm from the provided effects.

permitted_dep_add(model[, mode, dep, subset])

Computes which terms are permitted to be added to this model such that adding any of the returned terms does not violate the heredity constraints.

permitted_dep_drop(model[, mode, dep, subset])

Determines if the term specified by at idx of model can be dropped, given the other existing terms in the model, the mode, and the dependency matrix.

sample_model_dep_onebyone(dep, size[, ...])

Sample a model given the dependency matrix of a fixed size.

sample_model_dep_random(dep, size[, ...])

Sample a model given the dependency matrix of a fixed size.

term2strong(term, dep)

Convert an existing model to its strong heredity variant according to the provided dependency matrix.