BayesSIM (version 1.0.0)

nimTraceplot: Traceplot for BayesSIM

Description

Provides traceplot for objects of BayesSIM.

Usage

nimTraceplot(x, ...)

Value

Traceplots for MCMC samples are displayed. By default, the index vector and error variance are only included in the summary. Extra monitor variables are included, if specified.

Arguments

x

A fitted object of BayesSIM or individual model.

...

Further arguments passed to plot.

Examples

# \donttest{
simdata2 <- data.frame(DATA1$X, y = DATA1$y)

# 1. One tool version
fit_one <- BayesSIM(y ~ ., data = simdata2,
                    niter = 5000, nburnin = 1000, nchain = 1)

# Check median index vector estimates with standard errors
coef(fit_one, method = "median", se = TRUE)

# Fitted index values of median prediction
fitted(fit_one, type = "linpred", method = "median")

# Residuals of median prediction
residuals(fit_one, method = "median")

# Summary of the model
summary(fit_one)

# Convergence diagnostics
nimTraceplot(fit_one)

# Goodness of fit
GOF(fit_one)

# Fitted plot
plot(fit_one)

# Prediction with 95% credible interval at new data
newx <- data.frame(X1 = rnorm(10), X2 = rnorm(10), X3 = rnorm(10), X4 = rnorm(10))
pred <- predict(fit_one, newdata = newx, interval = "credible", level = 0.95)
plot(pred)


# 2. Split version
models <- BayesSIM_setup(y ~ ., data = simdata2)
Ccompile <- compileModelAndMCMC(models)
nimSampler <- get_sampler(Ccompile)
initList <- getInit(models)
mcmc.out <- runMCMC(nimSampler, niter = 5000, nburnin = 1000, thin = 1,
                    nchains = 1, setSeed = TRUE, inits = initList,
                    summary = TRUE, samplesAsCodaMCMC = TRUE)

# "fit_split" becomes exactly the same as the class of "fit_one" object and apply generic functions.
fit_split <- as_bsim(models, mcmc.out)

# }