TRMF (version 0.1.5)

TRMF_columns: Add a column regularization model to TRMF object

Description

Adds a regularization model to TRMF object created by create_TRMF() to constrain the fitting process of the coefficient matrix.

TRMF_coefficient is a (soon to be deprecated) alias for TRMF_columns.

Usage

TRMF_columns(obj,
    reg_type = c("l2", "nnls", "constrain", "interval", "none"), lambda = 0.0001)
TRMF_coefficients(obj,
    reg_type = c("l2", "nnls", "constrain", "interval", "none"), lambda = 0.0001)

Arguments

obj

TRMF object created by create_TRMF()

reg_type

regularization type to apply when fitting TRMF model. l2 regularizes by simple sum of squares, nnls forces coefficients to be non-negative. constrain constrains coefficients to be non-negative and to sum to 1. interval constrains coefficients to the interval [0-1]

lambda

L2 regularization parameter used for all regularization types. If NULL, uses lambda set in create_TRMF().

Value

Returns an updated object of class TRMF.

Details

This function doesn't do any computations, it just sets up regularization parameters for the coefficient matrix. This function should only be called once on a TRMF object. If called twice, it will overwrite previous model with a warning.

References

Yu, Hsiang-Fu, Nikhil Rao, and Inderjit S. Dhillon. "High-dimensional time series prediction with missing values." arXiv preprint arXiv:1509.08333 (2015).

See Also

train.TRMF, create_TRMF, TRMF_trend

Examples

# NOT RUN {
# create test data
xm = poly(x = (-10:10)/10,degree=4)
fm = matrix(abs(rnorm(40)),4,10)
Am = xm%*%fm+rnorm(210,0,.2)

# create model
obj = create_TRMF(Am)
obj = TRMF_columns(obj,reg_type ="nnls")
out = train(obj)
plot(out)


# }