BoostMLR (version 1.0.3)

plotBoostMLR: Plotting results across across the boosting iterations.

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.

Examples

# NOT RUN {
##-----------------------------------------------------------------
## 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")
# }