Multiple chains of MixNRMI1
multMixNRMI1(
x,
probs = c(0.025, 0.5, 0.975),
Alpha = 1,
Kappa = 0,
Gama = 0.4,
distr.k = "normal",
distr.p0 = "normal",
asigma = 0.5,
bsigma = 0.5,
delta_S = 3,
delta_U = 2,
Meps = 0.01,
Nx = 150,
Nit = 1500,
Pbi = 0.1,
epsilon = NULL,
printtime = TRUE,
extras = TRUE,
nchains = 4,
parallel = TRUE,
ncores = parallel::detectCores()
)
Numeric vector. Data set to which the density is fitted.
Numeric vector. Desired quantiles of the density estimates.
Numeric constant. Total mass of the centering measure. See details.
Numeric positive constant. See details.
Numeric constant. \(0\leq \texttt{Gama} \leq 1\). See details.
The distribution name for the kernel. Allowed names are "normal", "gamma", "beta", "double exponential", "lognormal" or their common abbreviations "norm", "exp", or an integer number identifying the mixture kernel: 1 = Normal; 2 = Gamma; 3 = Beta; 4 = Double Exponential; 5 = Lognormal.
The distribution name for the centering measure. Allowed names are "normal", "gamma", "beta", or their common abbreviations "norm", "exp", or an integer number identifying the centering measure: 1 = Normal; 2 = Gamma; 3 = Beta.
Numeric positive constant. Shape parameter of the gamma prior
on the standard deviation of the mixture kernel distr.k
.
Numeric positive constant. Rate parameter of the gamma prior
on the standard deviation of the mixture kernel distr.k
.
Numeric positive constant. Metropolis-Hastings proposal variation coefficient for sampling sigma.
Numeric positive constant. Metropolis-Hastings proposal variation coefficient for sampling the latent U.
Numeric constant. Relative error of the jump sizes in the continuous component of the process. Smaller values imply larger number of jumps.
Integer constant. Number of grid points for the evaluation of the density estimate.
Integer constant. Number of MCMC iterations.
Numeric constant. Burn-in period proportion of Nit.
Numeric constant. Extension to the evaluation grid range. See details.
Logical. If TRUE, prints out the execution time.
Logical. If TRUE, gives additional objects: means, weights and Js.
The number of chains to run.
Whether to run the chains in parallel. Only works on UNIX-like systems as it rests on Fork parallelism
Number of cores for the parallel run. Defaults to parallel::detectCores(), i.e. the maximum number of cores detected by R on your system.
a list containing the multiple fits.
# NOT RUN {
data(acidity)
multMixNRMI1(acidity, parallel = TRUE, Nit = 10, ncores = 2)
# }
Run the code above in your browser using DataLab