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TRMF (version 0.1.5)

Temporally Regularized Matrix Factorization

Description

Functions to estimate temporally regularized matrix factorizations (TRMF) for forecasting and imputing values in short but high-dimensional time series. Uses regularized alternating least squares to compute the factorization, allows for several types of constraints on matrix factors and natively handles weighted and missing data.

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Version

Install

install.packages('TRMF')

Monthly Downloads

70

Version

0.1.5

License

GPL-3

Maintainer

Chad Hammerquist

Last Published

August 16th, 2021

Functions in TRMF (0.1.5)

coef.TRMF

Extract TRMF Coefficients (Fm)
TRMF_regression

Add external regressors to TRMF object
TRMF_simple

Add L2 regularization model to a TRMF object
TRMF_columns

Add a column regularization model to TRMF object
NormalizeMatrix

Matrix Scaling
components.TRMF

Access TRMF factors
TRMF_es

Add exponential smoothing regularization model to a TRMF object.
TRMF_seasonal

Add seasonal regularization model to a TRMF object
TRMF_ar

Add an Auto-Regressive Regularization Model to a TRMF Object.
TRMF_trend

Add Trend Model to a TRMF Object
predict.TRMF

Predict method for TRMF model fit
plot.TRMF

Plot Latent Time Series for a TRMF Object
impute_TRMF

Impute missing values in a matrix
create_TRMF

Create a TRMF object
fitted.TRMF

Extract TRMF fitted values.
train.TRMF

Train a TRMF model
summary.TRMF

Summarize TRMF
reexports

Objects exported from other packages
retrain

Retrain TRMF objects.
residuals.TRMF

Extract TRMF residuals