plotBoostMLR: Plotting results across across the boosting iterations.

In BoostMLR: Boosting for Multivariate Longitudinal Responses

Description

Plotting training and test error, and estimate of variance/correlation parameters across the boosting iterations.

Usage

plotBoostMLR(Result,
             xlab = "",
             ylab = "",
             legend_fraction_x = 0.10,
             legend_fraction_y = 0,
             ...)

Arguments

Result	Result in the matrix form either training or test error, or estimate of variance/correlation parameters across the boosting iterations.
xlab	Label for the x-axis.
ylab	Label for the y-axis.
legend_fraction_x	Value use to expland the x-axis.
legend_fraction_y	Value use to expland the y-axis.
...	Further arguments passed to or from other methods.

Details

Plotting training and test error, and estimate of variance/correlation parameters across the boosting iterations.

Author(s)

Amol Pande and Hemant Ishwaran

Examples

##-----------------------------------------------------------------
## Multivariate Longitudinal Response
##-----------------------------------------------------------------

# Simulate data involves 3 response and 4 covariates

dta <- simLong(n = 100, N = 5, rho =.80, model = 1, q_x = 0, 
                                  q_y = 0,type = "corCompSym")$dtaL

# Boosting call: Raw values of covariates, B-spline for time, 
# no shrinkage, no estimate of rho and phi

boost.grow <- BoostMLR(x = dta$features, tm = dta$time, id = dta$id, 
                            y = dta$y, M = 100, VarFlag = FALSE)

# Plot training error
plotBoostMLR(boost.grow$Error_Rate,xlab = "m",ylab = "Training Error")

BoostMLR documentation built on Feb. 25, 2021, 5:06 p.m.