plot-methods: Plot method for the online_log_mixture class

In Nth-iteration-labs/ofmlr: Fit online finite mixtures of logistic regression models

Description

Plot an object of type online_log_mixture. This will only produce a plot when trace!=FALSE The plots will be of the log-likelihood of the model over the number of observations and the average change in L2 norm of the model parameters. Also, when params=TRUE plots of the parameter estimates over time will also be produced.

Will create a plot of each of the models stored in the model comparison class that you can browse one by one.

Usage

## S4 method for signature 'online_log_mixture,missing'
plot(x, y, params = FALSE,
  omit = 100, param.y = c(-5, 5), ...)

## S4 method for signature 'multi_online_log_mixture,missing'
plot(x, y, params = FALSE,
  omit = 100, param.y = c(-5, 5), ...)

Arguments

x	The online_log_mixture object
y	NULL
params	Boolean, if TRUE the trace of the parameter values will also be printed
omit	Number of observations to omit from the log likelihood and l2 Norm traces
.y	a vector with the min and max values of the plot of the beta parameters
x	An object of type multi_online_log_mixture
y	NULL
params	Boolean, if TRUE the trace of the parameter values will also be printed
omit	Number of observations to omit from the log likelihood and l2 Norm traces
.y	a vector with the min and max values of the plot of the beta parameters

Examples

M2 <- online_log_mixture(3,3, trace=1)
for(i in 1:10000){ 	
	X <- runif(3,-2,2)
	y <- rbinom(1, 1, inv_logit(c(0,-2,2)%*%X))
	M2 <- add_observation(M2, y, X, 0)
}
plot(M2, params=TRUE)

M1 <- online_log_mixture(2,1, trace=1)
models <- multi_online_log_mixture(M1)
models <- add_model(models, online_log_mixture(2,2, trace=1))
for(i in c(1:100)){
models <- add_observation(models, rbinom(1,1,.5), rnorm(2,0,1))
}
plot(models, params=TRUE, omit=0)

Nth-iteration-labs/ofmlr documentation built on Sept. 27, 2020, 9:49 p.m.