DirectLiNGAM: DirectLiNGAM class

In gkikuchi/rlingam: R Implementation of LiNGAM algorithms

Description

R implementation of direct LiNGAM algorithm

See reference for details of the algorithm

Super class

rlingam::LiNGAM -> DirectLiNGAM

Methods

Public methods

• DirectLiNGAM$fit()

• DirectLiNGAM$estimate_causal_order()

• DirectLiNGAM$search_exogenous_variable()

• DirectLiNGAM$residual()

• DirectLiNGAM$diff_mutual_info()

• DirectLiNGAM$entropy()

• DirectLiNGAM$clone()

Inherited methods

• rlingam::LiNGAM$estimate_adjacency_matrix()

• rlingam::LiNGAM$initialize()

• rlingam::LiNGAM$predict_adaptive_lasso()

---

Method fit()

fit DirectLiNGAM

Usage

DirectLiNGAM$fit(X)

Arguments

X

(numeric matrix or data.frame) data matrix to fit

---

Method estimate_causal_order()

search causal ordering

Usage

DirectLiNGAM$estimate_causal_order(X)

Arguments

X

(numerical matrix or data.frame) data matrix

---

Method search_exogenous_variable()

search exogenous variable

Usage

DirectLiNGAM$search_exogenous_variable(X, U)

Arguments

X

(numerical matrix or data.frame) data matrix

U

(numeric vector) index of each columns

Returns

index of estimated exogenous variable

---

Method residual()

residual when xi is regressed on xj

Usage

DirectLiNGAM$residual(xi, xj)

Arguments

xi

(numeric vector) target variable

xj

(numeric vector) explanatory variable

Returns

resid (numeric vector) calculated residual

---

Method diff_mutual_info()

calculate the difference of the mutual information

Usage

DirectLiNGAM$diff_mutual_info(xi_std, xj_std, ri_j, rj_i)

Arguments

xi_std

(numeric vector) standardized xi

xj_std

(numeric vector) standardized xj

ri_j

(numeric vector) resid of xi_std regressed on xj_std

rj_i

(numeric vector) resid of xj_std regressed on xi_std

Returns

scalar value of the difference of mutual information

---

Method entropy()

calculate entropy using maximum entropy approximation

Usage

DirectLiNGAM$entropy(u)

Arguments

u

(numeric vector) vector to calculate entropy

Returns

scalar value of entropy

---

Method clone()

The objects of this class are cloneable with this method.

Usage

DirectLiNGAM$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

References

S. Shimizu, T. Inazumi, Y. Sogawa, A. Hyvärinen, Y. Kawahara, T. Washio, P. O. Hoyer and K. Bollen. DirectLiNGAM: A direct method for learning a linear non-Gaussian structural equation model. Journal of Machine Learning Research, 12(Apr): 1225–1248, 2011.

gkikuchi/rlingam documentation built on Jan. 7, 2022, 11:10 p.m.