predict_FLC_given_PLC: Predict FLCs given new PLCs

In LICORS: Light Cone Reconstruction of States - Predictive State Estimation From Spatio-Temporal Data

Description

This function predicts FLCs given new PLCs based on the estimated ε mappings and estimated conditional distributions.

Usage

predict_FLC_given_PLC(train = list(data = list(FLC = NULL, PLC = NULL), 
    weight.matrix = NULL, pdfs = list(FLC = NULL, PLC = NULL)), test = list(PLC = NULL, 
    weight.matrix = NULL), type = c("weighted.mean", "mean", "median", "mode"), 
    method = list(FLC = "nonparametric", PLC = "normal"))

Arguments

train	a list of training examples with LC observations (a list of PLC and FLC), weight.matrix, and pdfs
test	a list of test examples with PLC observations and/or the weight.matrix associated with the PLC observations.
method	estimation method for estimating PLC and FLC distributions
type	prediction: 'mean', 'median', 'weightedmean', or 'mode'.

Value

N \times K matrix

LICORS documentation built on May 1, 2019, 10:13 p.m.