plot {LMest} | R Documentation |
Plots for Generalized Latent Markov Models
Description
Plots for outputs of LMest objects: LMbasic
, LMbasiccont
, LMlatent
, LMlatentcont
, and LMsearch
Usage
## S3 method for class 'LMbasic'
plot(x,
what = c("modSel", "CondProb", "transitions","marginal"),
verbose=interactive(),...)
## S3 method for class 'LMlatent'
plot(x,
what = c("modSel", "CondProb", "transitions","marginal"),
verbose=interactive(),...)
## S3 method for class 'LMbasiccont'
plot(x,
what = c("modSel", "density", "transitions","marginal"),
components,verbose=interactive(),...)
## S3 method for class 'LMlatentcont'
plot(x,
what = c("modSel", "density", "transitions","marginal"),
components, verbose=interactive(),...)
## S3 method for class 'LMsearch'
plot(x,...)
Arguments
x |
an object of class |
what |
a string indicating the type of plot. A detailed description is provided in the ‘Details’ section. |
components |
An integer or a vector of integers specifying the components (latent states) to be selected for the "density" plot. |
verbose |
A logical controlling if a text progress bar is displayed during the
fitting procedure. By default is |
... |
Unused argument. |
Details
The type of plots are the following:
"modSel" | plot of values of the Bayesian Information Criterion and of the Akaike Information |
Criterion for model selection | |
"CondProb" | plot of the estimated conditional response probabilities |
"density" | plot of the overall estimated density for continuous responses, with weights given by |
the estimated marginal distribution of the latent variable. For multivariate continuous | |
responses a contour plot is provided. If the argument components is specified, the |
|
density plot for the selected components results | |
"transitions" | path diagram of the estimated transition probabilities |
"marginal" | plot of the estimated marginal distribution of the latent variable |
If argument what
is not specified, a menu of choices is proposed in an interactive session.
Author(s)
Francesco Bartolucci, Silvia Pandolfi, Fulvia Pennoni, Alessio Farcomeni, Alessio Serafini
Examples
## Not run:
### Plot of basic LM model
data("data_SRHS_long")
SRHS <- data_SRHS_long[1:2400,]
# Categories rescaled to vary from 0 (“poor”) to 4 (“excellent”)
SRHS$srhs <- 5 - SRHS$srhs
out <- lmest(responsesFormula = srhs ~ NULL,
index = c("id","t"),
data = SRHS,
k = 1:3,
start = 1,
modBasic = 1,
seed = 123)
out
summary(out)
plot(out)
### Plot of basic LM model for continuous responses
data(data_long_cont)
out1 <- lmestCont(responsesFormula = Y1 + Y2 + Y3 ~ NULL,
index = c("id", "time"),
data = data_long_cont,
k = 1:5,
modBasic=1,
tol=10^-5)
plot(out1,what="modSel")
plot(out1,what="density")
plot(out1,what="density",components=c(1,3))
## End(Not run)